From 57c0dbccd302f9a093c8e9f21d2b0db0b381f3d9 Mon Sep 17 00:00:00 2001
From: kaustubh <kaustubh.mp007@gmail.com>
Date: Wed, 26 Aug 2026 22:54:20 +0530
Subject: [PATCH 1/4] feat: add
 ndarray/base/kernels/generic/binary-strided1d/unblocked

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description: Results of running static analysis checks when committing changes.
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---
---
 .../binary-strided1d/unblocked/README.md      | 1794 +++++++++++++++++
 .../binary-strided1d/unblocked/docs/repl.txt  |  510 +++++
 .../unblocked/examples/index.js               |  119 ++
 .../binary-strided1d/unblocked/lib/0d.js      |  137 ++
 .../binary-strided1d/unblocked/lib/10d.js     |  399 ++++
 .../binary-strided1d/unblocked/lib/1d.js      |  199 ++
 .../binary-strided1d/unblocked/lib/2d.js      |  237 +++
 .../binary-strided1d/unblocked/lib/3d.js      |  257 +++
 .../binary-strided1d/unblocked/lib/4d.js      |  277 +++
 .../binary-strided1d/unblocked/lib/5d.js      |  297 +++
 .../binary-strided1d/unblocked/lib/6d.js      |  319 +++
 .../binary-strided1d/unblocked/lib/7d.js      |  339 ++++
 .../binary-strided1d/unblocked/lib/8d.js      |  359 ++++
 .../binary-strided1d/unblocked/lib/9d.js      |  379 ++++
 .../binary-strided1d/unblocked/lib/index.js   |  175 ++
 .../binary-strided1d/unblocked/lib/main.js    |  185 ++
 .../binary-strided1d/unblocked/package.json   |   65 +
 .../binary-strided1d/unblocked/test/test.js   |   35 +
 18 files changed, 6082 insertions(+)
 create mode 100644 lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/README.md
 create mode 100644 lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/docs/repl.txt
 create mode 100644 lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/examples/index.js
 create mode 100644 lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/0d.js
 create mode 100644 lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/10d.js
 create mode 100644 lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/1d.js
 create mode 100644 lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/2d.js
 create mode 100644 lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/3d.js
 create mode 100644 lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/4d.js
 create mode 100644 lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/5d.js
 create mode 100644 lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/6d.js
 create mode 100644 lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/7d.js
 create mode 100644 lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/8d.js
 create mode 100644 lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/9d.js
 create mode 100644 lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/index.js
 create mode 100644 lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/main.js
 create mode 100644 lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/package.json
 create mode 100644 lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/test/test.js

diff --git a/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/README.md b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/README.md
new file mode 100644
index 000000000000..02a8d233eaca
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/README.md
@@ -0,0 +1,1794 @@
+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2026 The Stdlib Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+
+-->
+
+# kernel
+
+> Return a kernel for applying a one-dimensional strided array function to two input ndarrays and assigning results to an output ndarray.
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var kernel = require( '@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked' );
+```
+
+#### kernel( ndims )
+
+Returns a kernel for applying a one-dimensional strided array function to two input ndarrays and assigning results to an output ndarray.
+
+<!-- eslint-disable max-len -->
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+var gwxpy = require( '@stdlib/blas/ext/base/ndarray/gwxpy' );
+
+// Create data buffers:
+var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+var ybuf = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 ] );
+var zbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+
+// Define the array shapes:
+var xsh = [ 1, 3, 2, 2 ];
+var ysh = [ 1, 3, 2, 2 ];
+var zsh = [ 1, 3, 2, 2 ];
+
+// Define the array strides:
+var sx = [ 12, 4, 2, 1 ];
+var sy = [ 12, 4, 2, 1 ];
+var sz = [ 12, 4, 2, 1 ];
+
+// Define the index offsets:
+var ox = 0;
+var oy = 0;
+var oz = 0;
+
+// Create the input ndarray descriptors:
+var x = {
+    'dtype': 'float64',
+    'data': xbuf,
+    'shape': xsh,
+    'strides': sx,
+    'offset': ox,
+    'order': 'row-major'
+};
+
+var y = {
+    'dtype': 'float64',
+    'data': ybuf,
+    'shape': ysh,
+    'strides': sy,
+    'offset': oy,
+    'order': 'row-major'
+};
+
+// Create an output ndarray descriptor:
+var z = {
+    'dtype': 'float64',
+    'data': zbuf,
+    'shape': zsh,
+    'strides': sz,
+    'offset': oz,
+    'order': 'row-major'
+};
+
+// Initialize ndarray descriptors representing subarray views:
+var views = [
+    {
+        'dtype': x.dtype,
+        'data': x.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': x.offset,
+        'order': x.order
+    },
+    {
+        'dtype': y.dtype,
+        'data': y.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': y.offset,
+        'order': y.order
+    },
+    {
+        'dtype': z.dtype,
+        'data': z.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': z.offset,
+        'order': z.order
+    }
+];
+
+// Define an input strategy:
+function inputStrategy( x ) {
+    return {
+        'dtype': x.dtype,
+        'data': x.data,
+        'shape': [ 4 ],
+        'strides': [ 1 ],
+        'offset': x.offset,
+        'order': x.order
+    };
+}
+
+// Define an output strategy:
+function outputStrategy( x ) {
+    return x;
+}
+
+var strategy = {
+    'input': inputStrategy,
+    'output': outputStrategy
+};
+
+// Resolve a kernel:
+var f = kernel( 2 );
+
+// Apply strided function:
+f( gwxpy, [ x, y, z ], views, [ 1, 3 ], [ 12, 4 ], [ 12, 4 ], [ 12, 4 ], strategy, strategy, strategy, {} );
+
+var arr = ndarray2array( z.data, z.shape, z.strides, z.offset, z.order );
+// returns [ [ [ [ 3.0, 5.0 ], [ 7.0, 9.0 ] ], [ [ 11.0, 13.0 ], [ 15.0, 17.0 ] ], [ [ 19.0, 21.0 ], [ 23.0, 25.0 ] ] ] ]
+```
+
+The function accepts the following arguments:
+
+-   **ndims**: number of loop dimensions.
+
+If the function is provided an `ndims` value greater than the maximum number of supported loop dimensions, the function returns `null`.
+
+```javascript
+var f = kernel( 100000 );
+// returns null
+```
+
+The returned function accepts the following arguments:
+
+-   **fcn**: function which will be applied to two one-dimensional input subarrays and should update a one-dimensional output subarray with results.
+-   **arrays**: array containing two input ndarray [descriptors][@stdlib/ndarray/base/descriptor] and one output ndarray [descriptor][@stdlib/ndarray/base/descriptor], followed by any additional ndarray arguments.
+-   **views**: initialized ndarray [descriptors][@stdlib/ndarray/base/descriptor] representing subarray views.
+-   **shape**: loop dimensions.
+-   **stridesX**: loop dimension strides for the first input ndarray.
+-   **stridesY**: loop dimension strides for the second input ndarray.
+-   **stridesZ**: loop dimension strides for the output ndarray.
+-   **strategyX**: strategy for marshaling data to and from a first input ndarray view.
+-   **strategyY**: strategy for marshaling data to and from a second input ndarray view.
+-   **strategyZ**: strategy for marshaling data to and from an output ndarray view.
+-   **options**: function options which are passed through to `fcn`.
+
+The returned function iterates over ndarray elements according to the memory layout of the first input ndarray.
+
+<!-- lint disable maximum-heading-length -->
+
+#### kernel.kernel.kernel0d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
+
+<!-- lint enable maximum-heading-length -->
+
+Applies a one-dimensional strided array function to a list of specified dimensions in two input ndarrays and assigns results to a provided output ndarray.
+
+<!-- eslint-disable max-len -->
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+var gwxpy = require( '@stdlib/blas/ext/base/ndarray/gwxpy' );
+
+// Create data buffers:
+var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+var ybuf = new Float64Array( [ 2.0, 3.0, 4.0, 5.0 ] );
+var zbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );
+
+// Define the array shapes:
+var xsh = [ 2, 2 ];
+var ysh = [ 2, 2 ];
+var zsh = [ 2, 2 ];
+
+// Define the array strides:
+var sx = [ 2, 1 ];
+var sy = [ 2, 1 ];
+var sz = [ 2, 1 ];
+
+// Define the index offsets:
+var ox = 0;
+var oy = 0;
+var oz = 0;
+
+// Create the input ndarray descriptors:
+var x = {
+    'dtype': 'float64',
+    'data': xbuf,
+    'shape': xsh,
+    'strides': sx,
+    'offset': ox,
+    'order': 'row-major'
+};
+
+var y = {
+    'dtype': 'float64',
+    'data': ybuf,
+    'shape': ysh,
+    'strides': sy,
+    'offset': oy,
+    'order': 'row-major'
+};
+
+// Create an output ndarray descriptor:
+var z = {
+    'dtype': 'float64',
+    'data': zbuf,
+    'shape': zsh,
+    'strides': sz,
+    'offset': oz,
+    'order': 'row-major'
+};
+
+// Define an input strategy:
+function inputStrategy( x ) {
+    return {
+        'dtype': x.dtype,
+        'data': x.data,
+        'shape': [ 4 ],
+        'strides': [ 1 ],
+        'offset': x.offset,
+        'order': x.order
+    };
+}
+
+// Define an output strategy:
+function outputStrategy( x ) {
+    return x;
+}
+
+var strategy = {
+    'input': inputStrategy,
+    'output': outputStrategy
+};
+
+// Apply strided function:
+kernel.kernel0d( gwxpy, [ x, y, z ], [], [], [], [], [], strategy, strategy, strategy, {} );
+
+var v = z.data;
+// returns <Float64Array>[ 3.0, 5.0, 7.0, 9.0 ]
+```
+
+The function has the following parameters:
+
+-   **fcn**: function which will be applied to two one-dimensional input subarrays and should update a one-dimensional output subarray with results.
+-   **arrays**: array containing two input ndarray [descriptors][@stdlib/ndarray/base/descriptor] and one output ndarray [descriptor][@stdlib/ndarray/base/descriptor], followed by any additional ndarray arguments.
+-   **views**: initialized ndarray [descriptors][@stdlib/ndarray/base/descriptor] representing subarray views.
+-   **shape**: loop dimensions. Should have zero elements.
+-   **stridesX**: loop dimension strides for the first input ndarray.
+-   **stridesY**: loop dimension strides for the second input ndarray.
+-   **stridesZ**: loop dimension strides for the output ndarray.
+-   **strategyX**: strategy for marshaling data to and from a first input ndarray view.
+-   **strategyY**: strategy for marshaling data to and from a second input ndarray view.
+-   **strategyZ**: strategy for marshaling data to and from an output ndarray view.
+-   **options**: function options which are passed through to `fcn`.
+
+The `views`, `shape`, `stridesX`, `stridesY`, and `stridesZ` parameters are unused. Providing empty arrays for these parameters is recommended in order to ensure a monomorphic API.
+
+<!-- lint disable maximum-heading-length -->
+
+#### kernel.kernel.kernel1d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
+
+<!-- lint enable maximum-heading-length -->
+
+Applies a one-dimensional strided array function to a list of specified dimensions in two input ndarrays and assigns results to a provided output ndarray.
+
+<!-- eslint-disable max-len -->
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+var gwxpy = require( '@stdlib/blas/ext/base/ndarray/gwxpy' );
+
+// Create data buffers:
+var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+var ybuf = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 ] );
+var zbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+
+// Define the array shapes:
+var xsh = [ 3, 2, 2 ];
+var ysh = [ 3, 2, 2 ];
+var zsh = [ 3, 2, 2 ];
+
+// Define the array strides:
+var sx = [ 4, 2, 1 ];
+var sy = [ 4, 2, 1 ];
+var sz = [ 4, 2, 1 ];
+
+// Define the index offsets:
+var ox = 0;
+var oy = 0;
+var oz = 0;
+
+// Create the input ndarray descriptors:
+var x = {
+    'dtype': 'float64',
+    'data': xbuf,
+    'shape': xsh,
+    'strides': sx,
+    'offset': ox,
+    'order': 'row-major'
+};
+
+var y = {
+    'dtype': 'float64',
+    'data': ybuf,
+    'shape': ysh,
+    'strides': sy,
+    'offset': oy,
+    'order': 'row-major'
+};
+
+// Create an output ndarray descriptor:
+var z = {
+    'dtype': 'float64',
+    'data': zbuf,
+    'shape': zsh,
+    'strides': sz,
+    'offset': oz,
+    'order': 'row-major'
+};
+
+// Initialize ndarray descriptors representing subarray views:
+var views = [
+    {
+        'dtype': x.dtype,
+        'data': x.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': x.offset,
+        'order': x.order
+    },
+    {
+        'dtype': y.dtype,
+        'data': y.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': y.offset,
+        'order': y.order
+    },
+    {
+        'dtype': z.dtype,
+        'data': z.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': z.offset,
+        'order': z.order
+    }
+];
+
+// Define an input strategy:
+function inputStrategy( x ) {
+    return {
+        'dtype': x.dtype,
+        'data': x.data,
+        'shape': [ 4 ],
+        'strides': [ 1 ],
+        'offset': x.offset,
+        'order': x.order
+    };
+}
+
+// Define an output strategy:
+function outputStrategy( x ) {
+    return x;
+}
+
+var strategy = {
+    'input': inputStrategy,
+    'output': outputStrategy
+};
+
+// Apply strided function:
+kernel.kernel1d( gwxpy, [ x, y, z ], views, [ 3 ], [ 4 ], [ 4 ], [ 4 ], strategy, strategy, strategy, {} );
+
+var arr = ndarray2array( z.data, z.shape, z.strides, z.offset, z.order );
+// returns [ [ [ 3.0, 5.0 ], [ 7.0, 9.0 ] ], [ [ 11.0, 13.0 ], [ 15.0, 17.0 ] ], [ [ 19.0, 21.0 ], [ 23.0, 25.0 ] ] ]
+```
+
+The function has the following parameters:
+
+-   **fcn**: function which will be applied to two one-dimensional input subarrays and should update a one-dimensional output subarray with results.
+-   **arrays**: array containing two input ndarray [descriptors][@stdlib/ndarray/base/descriptor] and one output ndarray [descriptor][@stdlib/ndarray/base/descriptor], followed by any additional ndarray arguments.
+-   **views**: initialized ndarray [descriptors][@stdlib/ndarray/base/descriptor] representing subarray views.
+-   **shape**: loop dimensions. Should have one element.
+-   **stridesX**: loop dimension strides for the first input ndarray.
+-   **stridesY**: loop dimension strides for the second input ndarray.
+-   **stridesZ**: loop dimension strides for the output ndarray.
+-   **strategyX**: strategy for marshaling data to and from a first input ndarray view.
+-   **strategyY**: strategy for marshaling data to and from a second input ndarray view.
+-   **strategyZ**: strategy for marshaling data to and from an output ndarray view.
+-   **options**: function options which are passed through to `fcn`.
+
+<!-- lint disable maximum-heading-length -->
+
+#### kernel.kernel.kernel2d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
+
+<!-- lint enable maximum-heading-length -->
+
+Applies a one-dimensional strided array function to a list of specified dimensions in two input ndarrays and assigns results to a provided output ndarray.
+
+<!-- eslint-disable max-len -->
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+var gwxpy = require( '@stdlib/blas/ext/base/ndarray/gwxpy' );
+
+// Create data buffers:
+var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+var ybuf = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 ] );
+var zbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+
+// Define the array shapes:
+var xsh = [ 1, 3, 2, 2 ];
+var ysh = [ 1, 3, 2, 2 ];
+var zsh = [ 1, 3, 2, 2 ];
+
+// Define the array strides:
+var sx = [ 12, 4, 2, 1 ];
+var sy = [ 12, 4, 2, 1 ];
+var sz = [ 12, 4, 2, 1 ];
+
+// Define the index offsets:
+var ox = 0;
+var oy = 0;
+var oz = 0;
+
+// Create the input ndarray descriptors:
+var x = {
+    'dtype': 'float64',
+    'data': xbuf,
+    'shape': xsh,
+    'strides': sx,
+    'offset': ox,
+    'order': 'row-major'
+};
+
+var y = {
+    'dtype': 'float64',
+    'data': ybuf,
+    'shape': ysh,
+    'strides': sy,
+    'offset': oy,
+    'order': 'row-major'
+};
+
+// Create an output ndarray descriptor:
+var z = {
+    'dtype': 'float64',
+    'data': zbuf,
+    'shape': zsh,
+    'strides': sz,
+    'offset': oz,
+    'order': 'row-major'
+};
+
+// Initialize ndarray descriptors representing subarray views:
+var views = [
+    {
+        'dtype': x.dtype,
+        'data': x.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': x.offset,
+        'order': x.order
+    },
+    {
+        'dtype': y.dtype,
+        'data': y.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': y.offset,
+        'order': y.order
+    },
+    {
+        'dtype': z.dtype,
+        'data': z.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': z.offset,
+        'order': z.order
+    }
+];
+
+// Define an input strategy:
+function inputStrategy( x ) {
+    return {
+        'dtype': x.dtype,
+        'data': x.data,
+        'shape': [ 4 ],
+        'strides': [ 1 ],
+        'offset': x.offset,
+        'order': x.order
+    };
+}
+
+// Define an output strategy:
+function outputStrategy( x ) {
+    return x;
+}
+
+var strategy = {
+    'input': inputStrategy,
+    'output': outputStrategy
+};
+
+// Apply strided function:
+kernel.kernel2d( gwxpy, [ x, y, z ], views, [ 1, 3 ], [ 12, 4 ], [ 12, 4 ], [ 12, 4 ], strategy, strategy, strategy, {} );
+
+var arr = ndarray2array( z.data, z.shape, z.strides, z.offset, z.order );
+// returns [ [ [ [ 3.0, 5.0 ], [ 7.0, 9.0 ] ], [ [ 11.0, 13.0 ], [ 15.0, 17.0 ] ], [ [ 19.0, 21.0 ], [ 23.0, 25.0 ] ] ] ]
+```
+
+The function has the following parameters:
+
+-   **fcn**: function which will be applied to two one-dimensional input subarrays and should update a one-dimensional output subarray with results.
+-   **arrays**: array containing two input ndarray [descriptors][@stdlib/ndarray/base/descriptor] and one output ndarray [descriptor][@stdlib/ndarray/base/descriptor], followed by any additional ndarray arguments.
+-   **views**: initialized ndarray [descriptors][@stdlib/ndarray/base/descriptor] representing subarray views.
+-   **shape**: loop dimensions. Should have two elements.
+-   **stridesX**: loop dimension strides for the first input ndarray.
+-   **stridesY**: loop dimension strides for the second input ndarray.
+-   **stridesZ**: loop dimension strides for the output ndarray.
+-   **strategyX**: strategy for marshaling data to and from a first input ndarray view.
+-   **strategyY**: strategy for marshaling data to and from a second input ndarray view.
+-   **strategyZ**: strategy for marshaling data to and from an output ndarray view.
+-   **options**: function options which are passed through to `fcn`.
+
+<!-- lint disable maximum-heading-length -->
+
+#### kernel.kernel.kernel3d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
+
+<!-- lint enable maximum-heading-length -->
+
+Applies a one-dimensional strided array function to a list of specified dimensions in two input ndarrays and assigns results to a provided output ndarray.
+
+<!-- eslint-disable max-len -->
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+var gwxpy = require( '@stdlib/blas/ext/base/ndarray/gwxpy' );
+
+// Create data buffers:
+var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+var ybuf = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 ] );
+var zbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+
+// Define the array shapes:
+var xsh = [ 1, 1, 3, 2, 2 ];
+var ysh = [ 1, 1, 3, 2, 2 ];
+var zsh = [ 1, 1, 3, 2, 2 ];
+
+// Define the array strides:
+var sx = [ 12, 12, 4, 2, 1 ];
+var sy = [ 12, 12, 4, 2, 1 ];
+var sz = [ 12, 12, 4, 2, 1 ];
+
+// Define the index offsets:
+var ox = 0;
+var oy = 0;
+var oz = 0;
+
+// Create the input ndarray descriptors:
+var x = {
+    'dtype': 'float64',
+    'data': xbuf,
+    'shape': xsh,
+    'strides': sx,
+    'offset': ox,
+    'order': 'row-major'
+};
+
+var y = {
+    'dtype': 'float64',
+    'data': ybuf,
+    'shape': ysh,
+    'strides': sy,
+    'offset': oy,
+    'order': 'row-major'
+};
+
+// Create an output ndarray descriptor:
+var z = {
+    'dtype': 'float64',
+    'data': zbuf,
+    'shape': zsh,
+    'strides': sz,
+    'offset': oz,
+    'order': 'row-major'
+};
+
+// Initialize ndarray descriptors representing subarray views:
+var views = [
+    {
+        'dtype': x.dtype,
+        'data': x.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': x.offset,
+        'order': x.order
+    },
+    {
+        'dtype': y.dtype,
+        'data': y.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': y.offset,
+        'order': y.order
+    },
+    {
+        'dtype': z.dtype,
+        'data': z.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': z.offset,
+        'order': z.order
+    }
+];
+
+// Define an input strategy:
+function inputStrategy( x ) {
+    return {
+        'dtype': x.dtype,
+        'data': x.data,
+        'shape': [ 4 ],
+        'strides': [ 1 ],
+        'offset': x.offset,
+        'order': x.order
+    };
+}
+
+// Define an output strategy:
+function outputStrategy( x ) {
+    return x;
+}
+
+var strategy = {
+    'input': inputStrategy,
+    'output': outputStrategy
+};
+
+// Apply strided function:
+kernel.kernel3d( gwxpy, [ x, y, z ], views, [ 1, 1, 3 ], [ 12, 12, 4 ], [ 12, 12, 4 ], [ 12, 12, 4 ], strategy, strategy, strategy, {} );
+
+var arr = ndarray2array( z.data, z.shape, z.strides, z.offset, z.order );
+// returns [ [ [ [ [ 3.0, 5.0 ], [ 7.0, 9.0 ] ], [ [ 11.0, 13.0 ], [ 15.0, 17.0 ] ], [ [ 19.0, 21.0 ], [ 23.0, 25.0 ] ] ] ] ]
+```
+
+The function has the following parameters:
+
+-   **fcn**: function which will be applied to two one-dimensional input subarrays and should update a one-dimensional output subarray with results.
+-   **arrays**: array containing two input ndarray [descriptors][@stdlib/ndarray/base/descriptor] and one output ndarray [descriptor][@stdlib/ndarray/base/descriptor], followed by any additional ndarray arguments.
+-   **views**: initialized ndarray [descriptors][@stdlib/ndarray/base/descriptor] representing subarray views.
+-   **shape**: loop dimensions. Should have three elements.
+-   **stridesX**: loop dimension strides for the first input ndarray.
+-   **stridesY**: loop dimension strides for the second input ndarray.
+-   **stridesZ**: loop dimension strides for the output ndarray.
+-   **strategyX**: strategy for marshaling data to and from a first input ndarray view.
+-   **strategyY**: strategy for marshaling data to and from a second input ndarray view.
+-   **strategyZ**: strategy for marshaling data to and from an output ndarray view.
+-   **options**: function options which are passed through to `fcn`.
+
+<!-- lint disable maximum-heading-length -->
+
+#### kernel.kernel.kernel4d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
+
+<!-- lint enable maximum-heading-length -->
+
+Applies a one-dimensional strided array function to a list of specified dimensions in two input ndarrays and assigns results to a provided output ndarray.
+
+<!-- eslint-disable max-len -->
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+var gwxpy = require( '@stdlib/blas/ext/base/ndarray/gwxpy' );
+
+// Create data buffers:
+var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+var ybuf = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 ] );
+var zbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+
+// Define the array shapes:
+var xsh = [ 1, 1, 1, 3, 2, 2 ];
+var ysh = [ 1, 1, 1, 3, 2, 2 ];
+var zsh = [ 1, 1, 1, 3, 2, 2 ];
+
+// Define the array strides:
+var sx = [ 12, 12, 12, 4, 2, 1 ];
+var sy = [ 12, 12, 12, 4, 2, 1 ];
+var sz = [ 12, 12, 12, 4, 2, 1 ];
+
+// Define the index offsets:
+var ox = 0;
+var oy = 0;
+var oz = 0;
+
+// Create the input ndarray descriptors:
+var x = {
+    'dtype': 'float64',
+    'data': xbuf,
+    'shape': xsh,
+    'strides': sx,
+    'offset': ox,
+    'order': 'row-major'
+};
+
+var y = {
+    'dtype': 'float64',
+    'data': ybuf,
+    'shape': ysh,
+    'strides': sy,
+    'offset': oy,
+    'order': 'row-major'
+};
+
+// Create an output ndarray descriptor:
+var z = {
+    'dtype': 'float64',
+    'data': zbuf,
+    'shape': zsh,
+    'strides': sz,
+    'offset': oz,
+    'order': 'row-major'
+};
+
+// Initialize ndarray descriptors representing subarray views:
+var views = [
+    {
+        'dtype': x.dtype,
+        'data': x.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': x.offset,
+        'order': x.order
+    },
+    {
+        'dtype': y.dtype,
+        'data': y.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': y.offset,
+        'order': y.order
+    },
+    {
+        'dtype': z.dtype,
+        'data': z.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': z.offset,
+        'order': z.order
+    }
+];
+
+// Define an input strategy:
+function inputStrategy( x ) {
+    return {
+        'dtype': x.dtype,
+        'data': x.data,
+        'shape': [ 4 ],
+        'strides': [ 1 ],
+        'offset': x.offset,
+        'order': x.order
+    };
+}
+
+// Define an output strategy:
+function outputStrategy( x ) {
+    return x;
+}
+
+var strategy = {
+    'input': inputStrategy,
+    'output': outputStrategy
+};
+
+// Apply strided function:
+kernel.kernel4d( gwxpy, [ x, y, z ], views, [ 1, 1, 1, 3 ], [ 12, 12, 12, 4 ], [ 12, 12, 12, 4 ], [ 12, 12, 12, 4 ], strategy, strategy, strategy, {} );
+
+var arr = ndarray2array( z.data, z.shape, z.strides, z.offset, z.order );
+// returns [ [ [ [ [ [ 3.0, 5.0 ], [ 7.0, 9.0 ] ], [ [ 11.0, 13.0 ], [ 15.0, 17.0 ] ], [ [ 19.0, 21.0 ], [ 23.0, 25.0 ] ] ] ] ] ]
+```
+
+The function has the following parameters:
+
+-   **fcn**: function which will be applied to two one-dimensional input subarrays and should update a one-dimensional output subarray with results.
+-   **arrays**: array containing two input ndarray [descriptors][@stdlib/ndarray/base/descriptor] and one output ndarray [descriptor][@stdlib/ndarray/base/descriptor], followed by any additional ndarray arguments.
+-   **views**: initialized ndarray [descriptors][@stdlib/ndarray/base/descriptor] representing subarray views.
+-   **shape**: loop dimensions. Should have four elements.
+-   **stridesX**: loop dimension strides for the first input ndarray.
+-   **stridesY**: loop dimension strides for the second input ndarray.
+-   **stridesZ**: loop dimension strides for the output ndarray.
+-   **strategyX**: strategy for marshaling data to and from a first input ndarray view.
+-   **strategyY**: strategy for marshaling data to and from a second input ndarray view.
+-   **strategyZ**: strategy for marshaling data to and from an output ndarray view.
+-   **options**: function options which are passed through to `fcn`.
+
+<!-- lint disable maximum-heading-length -->
+
+#### kernel.kernel.kernel5d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
+
+<!-- lint enable maximum-heading-length -->
+
+Applies a one-dimensional strided array function to a list of specified dimensions in two input ndarrays and assigns results to a provided output ndarray.
+
+<!-- eslint-disable max-len -->
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+var gwxpy = require( '@stdlib/blas/ext/base/ndarray/gwxpy' );
+
+// Create data buffers:
+var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+var ybuf = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 ] );
+var zbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+
+// Define the array shapes:
+var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];
+var ysh = [ 1, 1, 1, 1, 3, 2, 2 ];
+var zsh = [ 1, 1, 1, 1, 3, 2, 2 ];
+
+// Define the array strides:
+var sx = [ 12, 12, 12, 12, 4, 2, 1 ];
+var sy = [ 12, 12, 12, 12, 4, 2, 1 ];
+var sz = [ 12, 12, 12, 12, 4, 2, 1 ];
+
+// Define the index offsets:
+var ox = 0;
+var oy = 0;
+var oz = 0;
+
+// Create the input ndarray descriptors:
+var x = {
+    'dtype': 'float64',
+    'data': xbuf,
+    'shape': xsh,
+    'strides': sx,
+    'offset': ox,
+    'order': 'row-major'
+};
+
+var y = {
+    'dtype': 'float64',
+    'data': ybuf,
+    'shape': ysh,
+    'strides': sy,
+    'offset': oy,
+    'order': 'row-major'
+};
+
+// Create an output ndarray descriptor:
+var z = {
+    'dtype': 'float64',
+    'data': zbuf,
+    'shape': zsh,
+    'strides': sz,
+    'offset': oz,
+    'order': 'row-major'
+};
+
+// Initialize ndarray descriptors representing subarray views:
+var views = [
+    {
+        'dtype': x.dtype,
+        'data': x.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': x.offset,
+        'order': x.order
+    },
+    {
+        'dtype': y.dtype,
+        'data': y.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': y.offset,
+        'order': y.order
+    },
+    {
+        'dtype': z.dtype,
+        'data': z.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': z.offset,
+        'order': z.order
+    }
+];
+
+// Define an input strategy:
+function inputStrategy( x ) {
+    return {
+        'dtype': x.dtype,
+        'data': x.data,
+        'shape': [ 4 ],
+        'strides': [ 1 ],
+        'offset': x.offset,
+        'order': x.order
+    };
+}
+
+// Define an output strategy:
+function outputStrategy( x ) {
+    return x;
+}
+
+var strategy = {
+    'input': inputStrategy,
+    'output': outputStrategy
+};
+
+// Apply strided function:
+kernel.kernel5d( gwxpy, [ x, y, z ], views, [ 1, 1, 1, 1, 3 ], [ 12, 12, 12, 12, 4 ], [ 12, 12, 12, 12, 4 ], [ 12, 12, 12, 12, 4 ], strategy, strategy, strategy, {} );
+
+var arr = ndarray2array( z.data, z.shape, z.strides, z.offset, z.order );
+// returns [ [ [ [ [ [ [ 3.0, 5.0 ], [ 7.0, 9.0 ] ], [ [ 11.0, 13.0 ], [ 15.0, 17.0 ] ], [ [ 19.0, 21.0 ], [ 23.0, 25.0 ] ] ] ] ] ] ]
+```
+
+The function has the following parameters:
+
+-   **fcn**: function which will be applied to two one-dimensional input subarrays and should update a one-dimensional output subarray with results.
+-   **arrays**: array containing two input ndarray [descriptors][@stdlib/ndarray/base/descriptor] and one output ndarray [descriptor][@stdlib/ndarray/base/descriptor], followed by any additional ndarray arguments.
+-   **views**: initialized ndarray [descriptors][@stdlib/ndarray/base/descriptor] representing subarray views.
+-   **shape**: loop dimensions. Should have five elements.
+-   **stridesX**: loop dimension strides for the first input ndarray.
+-   **stridesY**: loop dimension strides for the second input ndarray.
+-   **stridesZ**: loop dimension strides for the output ndarray.
+-   **strategyX**: strategy for marshaling data to and from a first input ndarray view.
+-   **strategyY**: strategy for marshaling data to and from a second input ndarray view.
+-   **strategyZ**: strategy for marshaling data to and from an output ndarray view.
+-   **options**: function options which are passed through to `fcn`.
+
+<!-- lint disable maximum-heading-length -->
+
+#### kernel.kernel.kernel6d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
+
+<!-- lint enable maximum-heading-length -->
+
+Applies a one-dimensional strided array function to a list of specified dimensions in two input ndarrays and assigns results to a provided output ndarray.
+
+<!-- eslint-disable max-len -->
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+var gwxpy = require( '@stdlib/blas/ext/base/ndarray/gwxpy' );
+
+// Create data buffers:
+var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+var ybuf = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 ] );
+var zbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+
+// Define the array shapes:
+var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];
+var ysh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];
+var zsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];
+
+// Define the array strides:
+var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];
+var sy = [ 12, 12, 12, 12, 12, 4, 2, 1 ];
+var sz = [ 12, 12, 12, 12, 12, 4, 2, 1 ];
+
+// Define the index offsets:
+var ox = 0;
+var oy = 0;
+var oz = 0;
+
+// Create the input ndarray descriptors:
+var x = {
+    'dtype': 'float64',
+    'data': xbuf,
+    'shape': xsh,
+    'strides': sx,
+    'offset': ox,
+    'order': 'row-major'
+};
+
+var y = {
+    'dtype': 'float64',
+    'data': ybuf,
+    'shape': ysh,
+    'strides': sy,
+    'offset': oy,
+    'order': 'row-major'
+};
+
+// Create an output ndarray descriptor:
+var z = {
+    'dtype': 'float64',
+    'data': zbuf,
+    'shape': zsh,
+    'strides': sz,
+    'offset': oz,
+    'order': 'row-major'
+};
+
+// Initialize ndarray descriptors representing subarray views:
+var views = [
+    {
+        'dtype': x.dtype,
+        'data': x.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': x.offset,
+        'order': x.order
+    },
+    {
+        'dtype': y.dtype,
+        'data': y.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': y.offset,
+        'order': y.order
+    },
+    {
+        'dtype': z.dtype,
+        'data': z.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': z.offset,
+        'order': z.order
+    }
+];
+
+// Define an input strategy:
+function inputStrategy( x ) {
+    return {
+        'dtype': x.dtype,
+        'data': x.data,
+        'shape': [ 4 ],
+        'strides': [ 1 ],
+        'offset': x.offset,
+        'order': x.order
+    };
+}
+
+// Define an output strategy:
+function outputStrategy( x ) {
+    return x;
+}
+
+var strategy = {
+    'input': inputStrategy,
+    'output': outputStrategy
+};
+
+// Apply strided function:
+kernel.kernel6d( gwxpy, [ x, y, z ], views, [ 1, 1, 1, 1, 1, 3 ], [ 12, 12, 12, 12, 12, 4 ], [ 12, 12, 12, 12, 12, 4 ], [ 12, 12, 12, 12, 12, 4 ], strategy, strategy, strategy, {} );
+
+var arr = ndarray2array( z.data, z.shape, z.strides, z.offset, z.order );
+// returns [ [ [ [ [ [ [ [ 3.0, 5.0 ], [ 7.0, 9.0 ] ], [ [ 11.0, 13.0 ], [ 15.0, 17.0 ] ], [ [ 19.0, 21.0 ], [ 23.0, 25.0 ] ] ] ] ] ] ] ]
+```
+
+The function has the following parameters:
+
+-   **fcn**: function which will be applied to two one-dimensional input subarrays and should update a one-dimensional output subarray with results.
+-   **arrays**: array containing two input ndarray [descriptors][@stdlib/ndarray/base/descriptor] and one output ndarray [descriptor][@stdlib/ndarray/base/descriptor], followed by any additional ndarray arguments.
+-   **views**: initialized ndarray [descriptors][@stdlib/ndarray/base/descriptor] representing subarray views.
+-   **shape**: loop dimensions. Should have six elements.
+-   **stridesX**: loop dimension strides for the first input ndarray.
+-   **stridesY**: loop dimension strides for the second input ndarray.
+-   **stridesZ**: loop dimension strides for the output ndarray.
+-   **strategyX**: strategy for marshaling data to and from a first input ndarray view.
+-   **strategyY**: strategy for marshaling data to and from a second input ndarray view.
+-   **strategyZ**: strategy for marshaling data to and from an output ndarray view.
+-   **options**: function options which are passed through to `fcn`.
+
+<!-- lint disable maximum-heading-length -->
+
+#### kernel.kernel.kernel7d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
+
+<!-- lint enable maximum-heading-length -->
+
+Applies a one-dimensional strided array function to a list of specified dimensions in two input ndarrays and assigns results to a provided output ndarray.
+
+<!-- eslint-disable max-len -->
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+var gwxpy = require( '@stdlib/blas/ext/base/ndarray/gwxpy' );
+
+// Create data buffers:
+var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+var ybuf = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 ] );
+var zbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+
+// Define the array shapes:
+var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];
+var ysh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];
+var zsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];
+
+// Define the array strides:
+var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];
+var sy = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];
+var sz = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];
+
+// Define the index offsets:
+var ox = 0;
+var oy = 0;
+var oz = 0;
+
+// Create the input ndarray descriptors:
+var x = {
+    'dtype': 'float64',
+    'data': xbuf,
+    'shape': xsh,
+    'strides': sx,
+    'offset': ox,
+    'order': 'row-major'
+};
+
+var y = {
+    'dtype': 'float64',
+    'data': ybuf,
+    'shape': ysh,
+    'strides': sy,
+    'offset': oy,
+    'order': 'row-major'
+};
+
+// Create an output ndarray descriptor:
+var z = {
+    'dtype': 'float64',
+    'data': zbuf,
+    'shape': zsh,
+    'strides': sz,
+    'offset': oz,
+    'order': 'row-major'
+};
+
+// Initialize ndarray descriptors representing subarray views:
+var views = [
+    {
+        'dtype': x.dtype,
+        'data': x.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': x.offset,
+        'order': x.order
+    },
+    {
+        'dtype': y.dtype,
+        'data': y.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': y.offset,
+        'order': y.order
+    },
+    {
+        'dtype': z.dtype,
+        'data': z.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': z.offset,
+        'order': z.order
+    }
+];
+
+// Define an input strategy:
+function inputStrategy( x ) {
+    return {
+        'dtype': x.dtype,
+        'data': x.data,
+        'shape': [ 4 ],
+        'strides': [ 1 ],
+        'offset': x.offset,
+        'order': x.order
+    };
+}
+
+// Define an output strategy:
+function outputStrategy( x ) {
+    return x;
+}
+
+var strategy = {
+    'input': inputStrategy,
+    'output': outputStrategy
+};
+
+// Apply strided function:
+kernel.kernel7d( gwxpy, [ x, y, z ], views, [ 1, 1, 1, 1, 1, 1, 3 ], [ 12, 12, 12, 12, 12, 12, 4 ], [ 12, 12, 12, 12, 12, 12, 4 ], [ 12, 12, 12, 12, 12, 12, 4 ], strategy, strategy, strategy, {} );
+
+var arr = ndarray2array( z.data, z.shape, z.strides, z.offset, z.order );
+// returns [ [ [ [ [ [ [ [ [ 3.0, 5.0 ], [ 7.0, 9.0 ] ], [ [ 11.0, 13.0 ], [ 15.0, 17.0 ] ], [ [ 19.0, 21.0 ], [ 23.0, 25.0 ] ] ] ] ] ] ] ] ]
+```
+
+The function has the following parameters:
+
+-   **fcn**: function which will be applied to two one-dimensional input subarrays and should update a one-dimensional output subarray with results.
+-   **arrays**: array containing two input ndarray [descriptors][@stdlib/ndarray/base/descriptor] and one output ndarray [descriptor][@stdlib/ndarray/base/descriptor], followed by any additional ndarray arguments.
+-   **views**: initialized ndarray [descriptors][@stdlib/ndarray/base/descriptor] representing subarray views.
+-   **shape**: loop dimensions. Should have seven elements.
+-   **stridesX**: loop dimension strides for the first input ndarray.
+-   **stridesY**: loop dimension strides for the second input ndarray.
+-   **stridesZ**: loop dimension strides for the output ndarray.
+-   **strategyX**: strategy for marshaling data to and from a first input ndarray view.
+-   **strategyY**: strategy for marshaling data to and from a second input ndarray view.
+-   **strategyZ**: strategy for marshaling data to and from an output ndarray view.
+-   **options**: function options which are passed through to `fcn`.
+
+<!-- lint disable maximum-heading-length -->
+
+#### kernel.kernel.kernel8d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
+
+<!-- lint enable maximum-heading-length -->
+
+Applies a one-dimensional strided array function to a list of specified dimensions in two input ndarrays and assigns results to a provided output ndarray.
+
+<!-- eslint-disable max-len -->
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+var gwxpy = require( '@stdlib/blas/ext/base/ndarray/gwxpy' );
+
+// Create data buffers:
+var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+var ybuf = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 ] );
+var zbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+
+// Define the array shapes:
+var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];
+var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];
+var zsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];
+
+// Define the array strides:
+var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];
+var sy = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];
+var sz = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];
+
+// Define the index offsets:
+var ox = 0;
+var oy = 0;
+var oz = 0;
+
+// Create the input ndarray descriptors:
+var x = {
+    'dtype': 'float64',
+    'data': xbuf,
+    'shape': xsh,
+    'strides': sx,
+    'offset': ox,
+    'order': 'row-major'
+};
+
+var y = {
+    'dtype': 'float64',
+    'data': ybuf,
+    'shape': ysh,
+    'strides': sy,
+    'offset': oy,
+    'order': 'row-major'
+};
+
+// Create an output ndarray descriptor:
+var z = {
+    'dtype': 'float64',
+    'data': zbuf,
+    'shape': zsh,
+    'strides': sz,
+    'offset': oz,
+    'order': 'row-major'
+};
+
+// Initialize ndarray descriptors representing subarray views:
+var views = [
+    {
+        'dtype': x.dtype,
+        'data': x.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': x.offset,
+        'order': x.order
+    },
+    {
+        'dtype': y.dtype,
+        'data': y.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': y.offset,
+        'order': y.order
+    },
+    {
+        'dtype': z.dtype,
+        'data': z.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': z.offset,
+        'order': z.order
+    }
+];
+
+// Define an input strategy:
+function inputStrategy( x ) {
+    return {
+        'dtype': x.dtype,
+        'data': x.data,
+        'shape': [ 4 ],
+        'strides': [ 1 ],
+        'offset': x.offset,
+        'order': x.order
+    };
+}
+
+// Define an output strategy:
+function outputStrategy( x ) {
+    return x;
+}
+
+var strategy = {
+    'input': inputStrategy,
+    'output': outputStrategy
+};
+
+// Apply strided function:
+kernel.kernel8d( gwxpy, [ x, y, z ], views, [ 1, 1, 1, 1, 1, 1, 1, 3 ], [ 12, 12, 12, 12, 12, 12, 12, 4 ], [ 12, 12, 12, 12, 12, 12, 12, 4 ], [ 12, 12, 12, 12, 12, 12, 12, 4 ], strategy, strategy, strategy, {} );
+
+var arr = ndarray2array( z.data, z.shape, z.strides, z.offset, z.order );
+// returns [ [ [ [ [ [ [ [ [ [ 3.0, 5.0 ], [ 7.0, 9.0 ] ], [ [ 11.0, 13.0 ], [ 15.0, 17.0 ] ], [ [ 19.0, 21.0 ], [ 23.0, 25.0 ] ] ] ] ] ] ] ] ] ]
+```
+
+The function has the following parameters:
+
+-   **fcn**: function which will be applied to two one-dimensional input subarrays and should update a one-dimensional output subarray with results.
+-   **arrays**: array containing two input ndarray [descriptors][@stdlib/ndarray/base/descriptor] and one output ndarray [descriptor][@stdlib/ndarray/base/descriptor], followed by any additional ndarray arguments.
+-   **views**: initialized ndarray [descriptors][@stdlib/ndarray/base/descriptor] representing subarray views.
+-   **shape**: loop dimensions. Should have eight elements.
+-   **stridesX**: loop dimension strides for the first input ndarray.
+-   **stridesY**: loop dimension strides for the second input ndarray.
+-   **stridesZ**: loop dimension strides for the output ndarray.
+-   **strategyX**: strategy for marshaling data to and from a first input ndarray view.
+-   **strategyY**: strategy for marshaling data to and from a second input ndarray view.
+-   **strategyZ**: strategy for marshaling data to and from an output ndarray view.
+-   **options**: function options which are passed through to `fcn`.
+
+<!-- lint disable maximum-heading-length -->
+
+#### kernel.kernel.kernel9d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
+
+<!-- lint enable maximum-heading-length -->
+
+Applies a one-dimensional strided array function to a list of specified dimensions in two input ndarrays and assigns results to a provided output ndarray.
+
+<!-- eslint-disable max-len -->
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+var gwxpy = require( '@stdlib/blas/ext/base/ndarray/gwxpy' );
+
+// Create data buffers:
+var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+var ybuf = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 ] );
+var zbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+
+// Define the array shapes:
+var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];
+var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];
+var zsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];
+
+// Define the array strides:
+var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];
+var sy = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];
+var sz = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];
+
+// Define the index offsets:
+var ox = 0;
+var oy = 0;
+var oz = 0;
+
+// Create the input ndarray descriptors:
+var x = {
+    'dtype': 'float64',
+    'data': xbuf,
+    'shape': xsh,
+    'strides': sx,
+    'offset': ox,
+    'order': 'row-major'
+};
+
+var y = {
+    'dtype': 'float64',
+    'data': ybuf,
+    'shape': ysh,
+    'strides': sy,
+    'offset': oy,
+    'order': 'row-major'
+};
+
+// Create an output ndarray descriptor:
+var z = {
+    'dtype': 'float64',
+    'data': zbuf,
+    'shape': zsh,
+    'strides': sz,
+    'offset': oz,
+    'order': 'row-major'
+};
+
+// Initialize ndarray descriptors representing subarray views:
+var views = [
+    {
+        'dtype': x.dtype,
+        'data': x.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': x.offset,
+        'order': x.order
+    },
+    {
+        'dtype': y.dtype,
+        'data': y.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': y.offset,
+        'order': y.order
+    },
+    {
+        'dtype': z.dtype,
+        'data': z.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': z.offset,
+        'order': z.order
+    }
+];
+
+// Define an input strategy:
+function inputStrategy( x ) {
+    return {
+        'dtype': x.dtype,
+        'data': x.data,
+        'shape': [ 4 ],
+        'strides': [ 1 ],
+        'offset': x.offset,
+        'order': x.order
+    };
+}
+
+// Define an output strategy:
+function outputStrategy( x ) {
+    return x;
+}
+
+var strategy = {
+    'input': inputStrategy,
+    'output': outputStrategy
+};
+
+// Apply strided function:
+kernel.kernel9d( gwxpy, [ x, y, z ], views, [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ], [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], strategy, strategy, strategy, {} );
+
+var arr = ndarray2array( z.data, z.shape, z.strides, z.offset, z.order );
+// returns [ [ [ [ [ [ [ [ [ [ [ 3.0, 5.0 ], [ 7.0, 9.0 ] ], [ [ 11.0, 13.0 ], [ 15.0, 17.0 ] ], [ [ 19.0, 21.0 ], [ 23.0, 25.0 ] ] ] ] ] ] ] ] ] ] ]
+```
+
+The function has the following parameters:
+
+-   **fcn**: function which will be applied to two one-dimensional input subarrays and should update a one-dimensional output subarray with results.
+-   **arrays**: array containing two input ndarray [descriptors][@stdlib/ndarray/base/descriptor] and one output ndarray [descriptor][@stdlib/ndarray/base/descriptor], followed by any additional ndarray arguments.
+-   **views**: initialized ndarray [descriptors][@stdlib/ndarray/base/descriptor] representing subarray views.
+-   **shape**: loop dimensions. Should have nine elements.
+-   **stridesX**: loop dimension strides for the first input ndarray.
+-   **stridesY**: loop dimension strides for the second input ndarray.
+-   **stridesZ**: loop dimension strides for the output ndarray.
+-   **strategyX**: strategy for marshaling data to and from a first input ndarray view.
+-   **strategyY**: strategy for marshaling data to and from a second input ndarray view.
+-   **strategyZ**: strategy for marshaling data to and from an output ndarray view.
+-   **options**: function options which are passed through to `fcn`.
+
+<!-- lint disable maximum-heading-length -->
+
+#### kernel.kernel.kernel10d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
+
+<!-- lint enable maximum-heading-length -->
+
+Applies a one-dimensional strided array function to a list of specified dimensions in two input ndarrays and assigns results to a provided output ndarray.
+
+<!-- eslint-disable max-len -->
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+var gwxpy = require( '@stdlib/blas/ext/base/ndarray/gwxpy' );
+
+// Create data buffers:
+var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+var ybuf = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 ] );
+var zbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+
+// Define the array shapes:
+var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];
+var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];
+var zsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];
+
+// Define the array strides:
+var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];
+var sy = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];
+var sz = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];
+
+// Define the index offsets:
+var ox = 0;
+var oy = 0;
+var oz = 0;
+
+// Create the input ndarray descriptors:
+var x = {
+    'dtype': 'float64',
+    'data': xbuf,
+    'shape': xsh,
+    'strides': sx,
+    'offset': ox,
+    'order': 'row-major'
+};
+
+var y = {
+    'dtype': 'float64',
+    'data': ybuf,
+    'shape': ysh,
+    'strides': sy,
+    'offset': oy,
+    'order': 'row-major'
+};
+
+// Create an output ndarray descriptor:
+var z = {
+    'dtype': 'float64',
+    'data': zbuf,
+    'shape': zsh,
+    'strides': sz,
+    'offset': oz,
+    'order': 'row-major'
+};
+
+// Initialize ndarray descriptors representing subarray views:
+var views = [
+    {
+        'dtype': x.dtype,
+        'data': x.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': x.offset,
+        'order': x.order
+    },
+    {
+        'dtype': y.dtype,
+        'data': y.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': y.offset,
+        'order': y.order
+    },
+    {
+        'dtype': z.dtype,
+        'data': z.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': z.offset,
+        'order': z.order
+    }
+];
+
+// Define an input strategy:
+function inputStrategy( x ) {
+    return {
+        'dtype': x.dtype,
+        'data': x.data,
+        'shape': [ 4 ],
+        'strides': [ 1 ],
+        'offset': x.offset,
+        'order': x.order
+    };
+}
+
+// Define an output strategy:
+function outputStrategy( x ) {
+    return x;
+}
+
+var strategy = {
+    'input': inputStrategy,
+    'output': outputStrategy
+};
+
+// Apply strided function:
+kernel.kernel10d( gwxpy, [ x, y, z ], views, [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ], [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], strategy, strategy, strategy, {} );
+
+var arr = ndarray2array( z.data, z.shape, z.strides, z.offset, z.order );
+// returns [ [ [ [ [ [ [ [ [ [ [ [ 3.0, 5.0 ], [ 7.0, 9.0 ] ], [ [ 11.0, 13.0 ], [ 15.0, 17.0 ] ], [ [ 19.0, 21.0 ], [ 23.0, 25.0 ] ] ] ] ] ] ] ] ] ] ] ]
+```
+
+The function has the following parameters:
+
+-   **fcn**: function which will be applied to two one-dimensional input subarrays and should update a one-dimensional output subarray with results.
+-   **arrays**: array containing two input ndarray [descriptors][@stdlib/ndarray/base/descriptor] and one output ndarray [descriptor][@stdlib/ndarray/base/descriptor], followed by any additional ndarray arguments.
+-   **views**: initialized ndarray [descriptors][@stdlib/ndarray/base/descriptor] representing subarray views.
+-   **shape**: loop dimensions. Should have ten elements.
+-   **stridesX**: loop dimension strides for the first input ndarray.
+-   **stridesY**: loop dimension strides for the second input ndarray.
+-   **stridesZ**: loop dimension strides for the output ndarray.
+-   **strategyX**: strategy for marshaling data to and from a first input ndarray view.
+-   **strategyY**: strategy for marshaling data to and from a second input ndarray view.
+-   **strategyZ**: strategy for marshaling data to and from an output ndarray view.
+-   **options**: function options which are passed through to `fcn`.
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   The strided array function is expected to have the following signature:
+
+    ```text
+    fcn( arrays[, options] )
+    ```
+
+    where
+
+    -   **arrays**: array containing a one-dimensional subarray of the first input ndarray, a one-dimensional subarray of the second input ndarray, a one-dimensional subarray of the output ndarray, and any additional ndarray arguments as subarrays.
+    -   **options**: function options (_optional_).
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint-disable max-len -->
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+var gwxpy = require( '@stdlib/blas/ext/base/ndarray/gwxpy' );
+var strategy = require( '@stdlib/ndarray/base/kernels/generic/unary-strided1d/strategy' );
+var kernel = require( '@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked' );
+
+// Create data buffers:
+var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+var ybuf = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 ] );
+var zbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+
+// Define the array shapes:
+var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];
+var ysh = [ 1, 1, 1, 1, 3, 2, 2 ];
+var zsh = [ 1, 1, 1, 1, 3, 2, 2 ];
+
+// Define the array strides:
+var sx = [ 12, 12, 12, 12, 4, 2, 1 ];
+var sy = [ 12, 12, 12, 12, 4, 2, 1 ];
+var sz = [ 12, 12, 12, 12, 4, 2, 1 ];
+
+// Define the index offsets:
+var ox = 0;
+var oy = 0;
+var oz = 0;
+
+// Create the input ndarray descriptors:
+var x = {
+    'dtype': 'float64',
+    'data': xbuf,
+    'shape': xsh,
+    'strides': sx,
+    'offset': ox,
+    'order': 'row-major'
+};
+
+var y = {
+    'dtype': 'float64',
+    'data': ybuf,
+    'shape': ysh,
+    'strides': sy,
+    'offset': oy,
+    'order': 'row-major'
+};
+
+// Create an output ndarray descriptor:
+var z = {
+    'dtype': 'float64',
+    'data': zbuf,
+    'shape': zsh,
+    'strides': sz,
+    'offset': oz,
+    'order': 'row-major'
+};
+
+// Initialize ndarray descriptors representing subarray views:
+var views = [
+    {
+        'dtype': x.dtype,
+        'data': x.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': x.offset,
+        'order': x.order
+    },
+    {
+        'dtype': y.dtype,
+        'data': y.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': y.offset,
+        'order': y.order
+    },
+    {
+        'dtype': z.dtype,
+        'data': z.data,
+        'shape': [ 2, 2 ],
+        'strides': [ 2, 1 ],
+        'offset': z.offset,
+        'order': z.order
+    }
+];
+
+// Resolve input/output strategies when iterating over subarray views:
+var strategyX = strategy( views[ 0 ] );
+var strategyY = strategy( views[ 1 ] );
+var strategyZ = strategy( views[ 2 ] );
+
+// Resolve a kernel:
+var f = kernel( 5 );
+
+// Apply strided function:
+f( gwxpy, [ x, y, z ], views, [ 1, 1, 1, 1, 3 ], [ 12, 12, 12, 12, 4 ], [ 12, 12, 12, 12, 4 ], [ 12, 12, 12, 12, 4 ], strategyX, strategyY, strategyZ, {} );
+
+console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) );
+console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) );
+console.log( ndarray2array( z.data, z.shape, z.strides, z.offset, z.order ) );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<section class="links">
+
+[@stdlib/ndarray/base/descriptor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/descriptor
+
+</section>
+
+<!-- /.links -->
diff --git a/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/docs/repl.txt b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/docs/repl.txt
new file mode 100644
index 000000000000..ef8d785a8002
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/docs/repl.txt
@@ -0,0 +1,510 @@
+{{alias}}( ndims )
+    Returns a kernel for applying a one-dimensional strided array function to
+    two input ndarrays and assigning results to an output ndarray.
+
+    The returned function has the following parameters:
+
+    - fcn: function which will be applied to two one-dimensional input
+    subarrays and should update a one-dimensional output subarray with results.
+    - arrays: array containing two input ndarray descriptors and one output
+    ndarray descriptor, followed by any additional ndarray arguments.
+    - views: initialized ndarray descriptors representing subarray views.
+    - shape: loop dimensions.
+    - stridesX: loop dimension strides for the first input ndarray.
+    - stridesY: loop dimension strides for the second input ndarray.
+    - stridesZ: loop dimension strides for the output ndarray.
+    - strategyX: strategy for marshaling data to and from a first input ndarray
+    view.
+    - strategyY: strategy for marshaling data to and from a second input ndarray
+    view.
+    - strategyZ: strategy for marshaling data to and from an output ndarray
+    view.
+    - options: function options which are passed through to `fcn`.
+
+    If `ndims` is greater than the maximum supported number of loop dimensions,
+    the function returns `null`.
+
+    Parameters
+    ----------
+    ndims: integer
+        Number of loop dimensions.
+
+    Returns
+    -------
+    fcn: Function|null
+        Kernel function.
+
+    Examples
+    --------
+    > var f = {{alias}}( 2 )
+    <Function>
+
+
+{{alias}}.kernel0d( fcn, arr, views, sh, sx, sy, sz, stX, stY, stZ, opts )
+    Applies a one-dimensional strided array function to a list of specified
+    dimensions in two input ndarrays and assigns results to a provided output
+    ndarray.
+
+    The `views`, `sh`, `sx`, `sy`, and `sz` parameters are unused. Providing
+    empty arrays for these parameters is recommended in order to ensure a
+    monomorphic API.
+
+    Parameters
+    ----------
+    fcn: Function
+        Wrapper for a one-dimensional strided array function.
+
+    arr: Array<Object>
+        Array containing two input ndarray descriptors and one output ndarray
+        descriptor, followed by any additional ndarray arguments.
+
+    views: Array<Object>
+        Initialized ndarray descriptors representing subarray views.
+
+    sh: Array<integer>
+        Loop dimensions. Should have zero elements.
+
+    sx: Array<integer>
+        Loop dimension strides for the first input ndarray.
+
+    sy: Array<integer>
+        Loop dimension strides for the second input ndarray.
+
+    sz: Array<integer>
+        Loop dimension strides for the output ndarray.
+
+    stX: Object
+        Strategy for marshaling data to and from a first input ndarray view.
+
+    stY: Object
+        Strategy for marshaling data to and from a second input ndarray view.
+
+    stZ: Object
+        Strategy for marshaling data to and from an output ndarray view.
+
+    opts: Object
+        Function options which are passed through to `fcn`.
+
+
+{{alias}}.kernel1d( fcn, arr, views, sh, sx, sy, sz, stX, stY, stZ, opts )
+    Applies a one-dimensional strided array function to a list of specified
+    dimensions in two input ndarrays and assigns results to a provided output
+    ndarray.
+
+    Parameters
+    ----------
+    fcn: Function
+        Wrapper for a one-dimensional strided array function.
+
+    arr: Array<Object>
+        Array containing two input ndarray descriptors and one output ndarray
+        descriptor, followed by any additional ndarray arguments.
+
+    views: Array<Object>
+        Initialized ndarray descriptors representing subarray views.
+
+    sh: Array<integer>
+        Loop dimensions. Should have one element.
+
+    sx: Array<integer>
+        Loop dimension strides for the first input ndarray.
+
+    sy: Array<integer>
+        Loop dimension strides for the second input ndarray.
+
+    sz: Array<integer>
+        Loop dimension strides for the output ndarray.
+
+    stX: Object
+        Strategy for marshaling data to and from a first input ndarray view.
+
+    stY: Object
+        Strategy for marshaling data to and from a second input ndarray view.
+
+    stZ: Object
+        Strategy for marshaling data to and from an output ndarray view.
+
+    opts: Object
+        Function options which are passed through to `fcn`.
+
+
+{{alias}}.kernel2d( fcn, arr, views, sh, sx, sy, sz, stX, stY, stZ, opts )
+    Applies a one-dimensional strided array function to a list of specified
+    dimensions in two input ndarrays and assigns results to a provided output
+    ndarray.
+
+    Parameters
+    ----------
+    fcn: Function
+        Wrapper for a one-dimensional strided array function.
+
+    arr: Array<Object>
+        Array containing two input ndarray descriptors and one output ndarray
+        descriptor, followed by any additional ndarray arguments.
+
+    views: Array<Object>
+        Initialized ndarray descriptors representing subarray views.
+
+    sh: Array<integer>
+        Loop dimensions. Should have two elements.
+
+    sx: Array<integer>
+        Loop dimension strides for the first input ndarray.
+
+    sy: Array<integer>
+        Loop dimension strides for the second input ndarray.
+
+    sz: Array<integer>
+        Loop dimension strides for the output ndarray.
+
+    stX: Object
+        Strategy for marshaling data to and from a first input ndarray view.
+
+    stY: Object
+        Strategy for marshaling data to and from a second input ndarray view.
+
+    stZ: Object
+        Strategy for marshaling data to and from an output ndarray view.
+
+    opts: Object
+        Function options which are passed through to `fcn`.
+
+
+{{alias}}.kernel3d( fcn, arr, views, sh, sx, sy, sz, stX, stY, stZ, opts )
+    Applies a one-dimensional strided array function to a list of specified
+    dimensions in two input ndarrays and assigns results to a provided output
+    ndarray.
+
+    Parameters
+    ----------
+    fcn: Function
+        Wrapper for a one-dimensional strided array function.
+
+    arr: Array<Object>
+        Array containing two input ndarray descriptors and one output ndarray
+        descriptor, followed by any additional ndarray arguments.
+
+    views: Array<Object>
+        Initialized ndarray descriptors representing subarray views.
+
+    sh: Array<integer>
+        Loop dimensions. Should have three elements.
+
+    sx: Array<integer>
+        Loop dimension strides for the first input ndarray.
+
+    sy: Array<integer>
+        Loop dimension strides for the second input ndarray.
+
+    sz: Array<integer>
+        Loop dimension strides for the output ndarray.
+
+    stX: Object
+        Strategy for marshaling data to and from a first input ndarray view.
+
+    stY: Object
+        Strategy for marshaling data to and from a second input ndarray view.
+
+    stZ: Object
+        Strategy for marshaling data to and from an output ndarray view.
+
+    opts: Object
+        Function options which are passed through to `fcn`.
+
+
+{{alias}}.kernel4d( fcn, arr, views, sh, sx, sy, sz, stX, stY, stZ, opts )
+    Applies a one-dimensional strided array function to a list of specified
+    dimensions in two input ndarrays and assigns results to a provided output
+    ndarray.
+
+    Parameters
+    ----------
+    fcn: Function
+        Wrapper for a one-dimensional strided array function.
+
+    arr: Array<Object>
+        Array containing two input ndarray descriptors and one output ndarray
+        descriptor, followed by any additional ndarray arguments.
+
+    views: Array<Object>
+        Initialized ndarray descriptors representing subarray views.
+
+    sh: Array<integer>
+        Loop dimensions. Should have four elements.
+
+    sx: Array<integer>
+        Loop dimension strides for the first input ndarray.
+
+    sy: Array<integer>
+        Loop dimension strides for the second input ndarray.
+
+    sz: Array<integer>
+        Loop dimension strides for the output ndarray.
+
+    stX: Object
+        Strategy for marshaling data to and from a first input ndarray view.
+
+    stY: Object
+        Strategy for marshaling data to and from a second input ndarray view.
+
+    stZ: Object
+        Strategy for marshaling data to and from an output ndarray view.
+
+    opts: Object
+        Function options which are passed through to `fcn`.
+
+
+{{alias}}.kernel5d( fcn, arr, views, sh, sx, sy, sz, stX, stY, stZ, opts )
+    Applies a one-dimensional strided array function to a list of specified
+    dimensions in two input ndarrays and assigns results to a provided output
+    ndarray.
+
+    Parameters
+    ----------
+    fcn: Function
+        Wrapper for a one-dimensional strided array function.
+
+    arr: Array<Object>
+        Array containing two input ndarray descriptors and one output ndarray
+        descriptor, followed by any additional ndarray arguments.
+
+    views: Array<Object>
+        Initialized ndarray descriptors representing subarray views.
+
+    sh: Array<integer>
+        Loop dimensions. Should have five elements.
+
+    sx: Array<integer>
+        Loop dimension strides for the first input ndarray.
+
+    sy: Array<integer>
+        Loop dimension strides for the second input ndarray.
+
+    sz: Array<integer>
+        Loop dimension strides for the output ndarray.
+
+    stX: Object
+        Strategy for marshaling data to and from a first input ndarray view.
+
+    stY: Object
+        Strategy for marshaling data to and from a second input ndarray view.
+
+    stZ: Object
+        Strategy for marshaling data to and from an output ndarray view.
+
+    opts: Object
+        Function options which are passed through to `fcn`.
+
+
+{{alias}}.kernel6d( fcn, arr, views, sh, sx, sy, sz, stX, stY, stZ, opts )
+    Applies a one-dimensional strided array function to a list of specified
+    dimensions in two input ndarrays and assigns results to a provided output
+    ndarray.
+
+    Parameters
+    ----------
+    fcn: Function
+        Wrapper for a one-dimensional strided array function.
+
+    arr: Array<Object>
+        Array containing two input ndarray descriptors and one output ndarray
+        descriptor, followed by any additional ndarray arguments.
+
+    views: Array<Object>
+        Initialized ndarray descriptors representing subarray views.
+
+    sh: Array<integer>
+        Loop dimensions. Should have six elements.
+
+    sx: Array<integer>
+        Loop dimension strides for the first input ndarray.
+
+    sy: Array<integer>
+        Loop dimension strides for the second input ndarray.
+
+    sz: Array<integer>
+        Loop dimension strides for the output ndarray.
+
+    stX: Object
+        Strategy for marshaling data to and from a first input ndarray view.
+
+    stY: Object
+        Strategy for marshaling data to and from a second input ndarray view.
+
+    stZ: Object
+        Strategy for marshaling data to and from an output ndarray view.
+
+    opts: Object
+        Function options which are passed through to `fcn`.
+
+
+{{alias}}.kernel7d( fcn, arr, views, sh, sx, sy, sz, stX, stY, stZ, opts )
+    Applies a one-dimensional strided array function to a list of specified
+    dimensions in two input ndarrays and assigns results to a provided output
+    ndarray.
+
+    Parameters
+    ----------
+    fcn: Function
+        Wrapper for a one-dimensional strided array function.
+
+    arr: Array<Object>
+        Array containing two input ndarray descriptors and one output ndarray
+        descriptor, followed by any additional ndarray arguments.
+
+    views: Array<Object>
+        Initialized ndarray descriptors representing subarray views.
+
+    sh: Array<integer>
+        Loop dimensions. Should have seven elements.
+
+    sx: Array<integer>
+        Loop dimension strides for the first input ndarray.
+
+    sy: Array<integer>
+        Loop dimension strides for the second input ndarray.
+
+    sz: Array<integer>
+        Loop dimension strides for the output ndarray.
+
+    stX: Object
+        Strategy for marshaling data to and from a first input ndarray view.
+
+    stY: Object
+        Strategy for marshaling data to and from a second input ndarray view.
+
+    stZ: Object
+        Strategy for marshaling data to and from an output ndarray view.
+
+    opts: Object
+        Function options which are passed through to `fcn`.
+
+
+{{alias}}.kernel8d( fcn, arr, views, sh, sx, sy, sz, stX, stY, stZ, opts )
+    Applies a one-dimensional strided array function to a list of specified
+    dimensions in two input ndarrays and assigns results to a provided output
+    ndarray.
+
+    Parameters
+    ----------
+    fcn: Function
+        Wrapper for a one-dimensional strided array function.
+
+    arr: Array<Object>
+        Array containing two input ndarray descriptors and one output ndarray
+        descriptor, followed by any additional ndarray arguments.
+
+    views: Array<Object>
+        Initialized ndarray descriptors representing subarray views.
+
+    sh: Array<integer>
+        Loop dimensions. Should have eight elements.
+
+    sx: Array<integer>
+        Loop dimension strides for the first input ndarray.
+
+    sy: Array<integer>
+        Loop dimension strides for the second input ndarray.
+
+    sz: Array<integer>
+        Loop dimension strides for the output ndarray.
+
+    stX: Object
+        Strategy for marshaling data to and from a first input ndarray view.
+
+    stY: Object
+        Strategy for marshaling data to and from a second input ndarray view.
+
+    stZ: Object
+        Strategy for marshaling data to and from an output ndarray view.
+
+    opts: Object
+        Function options which are passed through to `fcn`.
+
+
+{{alias}}.kernel9d( fcn, arr, views, sh, sx, sy, sz, stX, stY, stZ, opts )
+    Applies a one-dimensional strided array function to a list of specified
+    dimensions in two input ndarrays and assigns results to a provided output
+    ndarray.
+
+    Parameters
+    ----------
+    fcn: Function
+        Wrapper for a one-dimensional strided array function.
+
+    arr: Array<Object>
+        Array containing two input ndarray descriptors and one output ndarray
+        descriptor, followed by any additional ndarray arguments.
+
+    views: Array<Object>
+        Initialized ndarray descriptors representing subarray views.
+
+    sh: Array<integer>
+        Loop dimensions. Should have nine elements.
+
+    sx: Array<integer>
+        Loop dimension strides for the first input ndarray.
+
+    sy: Array<integer>
+        Loop dimension strides for the second input ndarray.
+
+    sz: Array<integer>
+        Loop dimension strides for the output ndarray.
+
+    stX: Object
+        Strategy for marshaling data to and from a first input ndarray view.
+
+    stY: Object
+        Strategy for marshaling data to and from a second input ndarray view.
+
+    stZ: Object
+        Strategy for marshaling data to and from an output ndarray view.
+
+    opts: Object
+        Function options which are passed through to `fcn`.
+
+
+{{alias}}.kernel10d( fcn, arr, views, sh, sx, sy, sz, stX, stY, stZ, opts )
+    Applies a one-dimensional strided array function to a list of specified
+    dimensions in two input ndarrays and assigns results to a provided output
+    ndarray.
+
+    Parameters
+    ----------
+    fcn: Function
+        Wrapper for a one-dimensional strided array function.
+
+    arr: Array<Object>
+        Array containing two input ndarray descriptors and one output ndarray
+        descriptor, followed by any additional ndarray arguments.
+
+    views: Array<Object>
+        Initialized ndarray descriptors representing subarray views.
+
+    sh: Array<integer>
+        Loop dimensions. Should have ten elements.
+
+    sx: Array<integer>
+        Loop dimension strides for the first input ndarray.
+
+    sy: Array<integer>
+        Loop dimension strides for the second input ndarray.
+
+    sz: Array<integer>
+        Loop dimension strides for the output ndarray.
+
+    stX: Object
+        Strategy for marshaling data to and from a first input ndarray view.
+
+    stY: Object
+        Strategy for marshaling data to and from a second input ndarray view.
+
+    stZ: Object
+        Strategy for marshaling data to and from an output ndarray view.
+
+    opts: Object
+        Function options which are passed through to `fcn`.
+
+    See Also
+    --------
+
diff --git a/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/examples/index.js b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/examples/index.js
new file mode 100644
index 000000000000..62a43de2234c
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/examples/index.js
@@ -0,0 +1,119 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/* eslint-disable max-len */
+
+'use strict';
+
+var Float64Array = require( '@stdlib/array/float64' );
+var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+var gwxpy = require( '@stdlib/blas/ext/base/ndarray/gwxpy' );
+var strategy = require( '@stdlib/ndarray/base/kernels/generic/unary-strided1d/strategy' );
+var kernel = require( './../lib' );
+
+// Create data buffers:
+var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+var ybuf = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 ] );
+var zbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+
+// Define the array shapes:
+var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];
+var ysh = [ 1, 1, 1, 1, 3, 2, 2 ];
+var zsh = [ 1, 1, 1, 1, 3, 2, 2 ];
+
+// Define the array strides:
+var sx = [ 12, 12, 12, 12, 4, 2, 1 ];
+var sy = [ 12, 12, 12, 12, 4, 2, 1 ];
+var sz = [ 12, 12, 12, 12, 4, 2, 1 ];
+
+// Define the index offsets:
+var ox = 0;
+var oy = 0;
+var oz = 0;
+
+// Create the input ndarray descriptors:
+var x = {
+	'dtype': 'float64',
+	'data': xbuf,
+	'shape': xsh,
+	'strides': sx,
+	'offset': ox,
+	'order': 'row-major'
+};
+
+var y = {
+	'dtype': 'float64',
+	'data': ybuf,
+	'shape': ysh,
+	'strides': sy,
+	'offset': oy,
+	'order': 'row-major'
+};
+
+// Create an output ndarray descriptor:
+var z = {
+	'dtype': 'float64',
+	'data': zbuf,
+	'shape': zsh,
+	'strides': sz,
+	'offset': oz,
+	'order': 'row-major'
+};
+
+// Initialize ndarray descriptors representing subarray views:
+var views = [
+	{
+		'dtype': x.dtype,
+		'data': x.data,
+		'shape': [ 2, 2 ],
+		'strides': [ 2, 1 ],
+		'offset': x.offset,
+		'order': x.order
+	},
+	{
+		'dtype': y.dtype,
+		'data': y.data,
+		'shape': [ 2, 2 ],
+		'strides': [ 2, 1 ],
+		'offset': y.offset,
+		'order': y.order
+	},
+	{
+		'dtype': z.dtype,
+		'data': z.data,
+		'shape': [ 2, 2 ],
+		'strides': [ 2, 1 ],
+		'offset': z.offset,
+		'order': z.order
+	}
+];
+
+// Resolve input/output strategies when iterating over subarray views:
+var strategyX = strategy( views[ 0 ] );
+var strategyY = strategy( views[ 1 ] );
+var strategyZ = strategy( views[ 2 ] );
+
+// Resolve a kernel:
+var f = kernel( 5 );
+
+// Apply strided function:
+f( gwxpy, [ x, y, z ], views, [ 1, 1, 1, 1, 3 ], [ 12, 12, 12, 12, 4 ], [ 12, 12, 12, 12, 4 ], [ 12, 12, 12, 12, 4 ], strategyX, strategyY, strategyZ, {} );
+
+console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) );
+console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) );
+console.log( ndarray2array( z.data, z.shape, z.strides, z.offset, z.order ) );
diff --git a/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/0d.js b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/0d.js
new file mode 100644
index 000000000000..ec56e91e19f3
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/0d.js
@@ -0,0 +1,137 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MAIN //
+
+/**
+* Applies a one-dimensional strided array function to a list of specified dimensions in two input ndarrays and assigns results to a provided output ndarray.
+*
+* ## Notes
+*
+* -   The `views`, `shape`, `stridesX`, `stridesY`, and `stridesZ` parameters are unused. Providing empty arrays for these parameters is recommended in order to ensure a monomorphic API.
+*
+* @private
+* @param {Function} fcn - wrapper for a one-dimensional strided array function
+* @param {Array<Object>} arrays - ndarray descriptors
+* @param {Array<Object>} views - initialized ndarray descriptors representing subarray views
+* @param {Array<integer>} shape - loop dimensions
+* @param {Array<integer>} stridesX - loop dimension strides for the first input ndarray
+* @param {Array<integer>} stridesY - loop dimension strides for the second input ndarray
+* @param {Array<integer>} stridesZ - loop dimension strides for the output ndarray
+* @param {Object} strategyX - strategy for marshaling data to and from a first input ndarray view
+* @param {Object} strategyY - strategy for marshaling data to and from a second input ndarray view
+* @param {Object} strategyZ - strategy for marshaling data to and from an output ndarray view
+* @param {Options} opts - function options
+* @returns {void}
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+* var gwxpy = require( '@stdlib/blas/ext/base/ndarray/gwxpy' );
+*
+* // Create data buffers:
+* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
+* var ybuf = new Float64Array( [ 2.0, 3.0, 4.0, 5.0 ] );
+* var zbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );
+*
+* // Define the array shapes:
+* var xsh = [ 2, 2 ];
+* var ysh = [ 2, 2 ];
+* var zsh = [ 2, 2 ];
+*
+* // Define the array strides:
+* var sx = [ 2, 1 ];
+* var sy = [ 2, 1 ];
+* var sz = [ 2, 1 ];
+*
+* // Define the index offsets:
+* var ox = 0;
+* var oy = 0;
+* var oz = 0;
+*
+* // Create the input ndarray descriptors:
+* var x = {
+*     'dtype': 'float64',
+*     'data': xbuf,
+*     'shape': xsh,
+*     'strides': sx,
+*     'offset': ox,
+*     'order': 'row-major'
+* };
+*
+* var y = {
+*     'dtype': 'float64',
+*     'data': ybuf,
+*     'shape': ysh,
+*     'strides': sy,
+*     'offset': oy,
+*     'order': 'row-major'
+* };
+*
+* // Create an output ndarray descriptor:
+* var z = {
+*     'dtype': 'float64',
+*     'data': zbuf,
+*     'shape': zsh,
+*     'strides': sz,
+*     'offset': oz,
+*     'order': 'row-major'
+* };
+*
+* // Define an input strategy:
+* function inputStrategy( x ) {
+*     return {
+*         'dtype': x.dtype,
+*         'data': x.data,
+*         'shape': [ 4 ],
+*         'strides': [ 1 ],
+*         'offset': x.offset,
+*         'order': x.order
+*     };
+* }
+*
+* // Define an output strategy:
+* function outputStrategy( x ) {
+*     return x;
+* }
+*
+* var strategy = {
+*     'input': inputStrategy,
+*     'output': outputStrategy
+* };
+*
+* // Apply strided function:
+* kernel( gwxpy, [ x, y, z ], [], [], [], [], [], strategy, strategy, strategy, {} );
+*
+* var v = z.data;
+* // returns <Float64Array>[ 3.0, 5.0, 7.0, 9.0 ]
+*/
+function kernel( fcn, arrays, views, shape, stridesX, stridesY, stridesZ, strategyX, strategyY, strategyZ, opts ) { // eslint-disable-line max-len, max-params
+	arrays[ 0 ] = strategyX.input( arrays[ 0 ] );
+	arrays[ 1 ] = strategyY.input( arrays[ 1 ] );
+	arrays[ 2 ] = strategyZ.input( arrays[ 2 ] );
+	fcn( arrays, opts );
+	strategyZ.output( arrays[ 2 ] );
+}
+
+
+// EXPORTS //
+
+module.exports = kernel;
diff --git a/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/10d.js b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/10d.js
new file mode 100644
index 000000000000..1155559498df
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/10d.js
@@ -0,0 +1,399 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/* eslint-disable max-depth, max-len */
+
+'use strict';
+
+// MODULES //
+
+var isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major' );
+var copyIndexed = require( '@stdlib/array/base/copy-indexed' );
+var incrementOffsets = require( '@stdlib/ndarray/base/kernels/utils/increment-offsets' );
+var setViewOffsets = require( '@stdlib/ndarray/base/set-descriptor-offsets' );
+var offsets = require( '@stdlib/ndarray/base/offsets' );
+
+
+// MAIN //
+
+/**
+* Applies a one-dimensional strided array function to a list of specified dimensions in two input ndarrays and assigns results to a provided output ndarray.
+*
+* @private
+* @param {Function} fcn - wrapper for a one-dimensional strided array function
+* @param {Array<Object>} arrays - ndarray descriptors
+* @param {Array<Object>} views - initialized ndarray descriptors representing subarray views
+* @param {Array<integer>} shape - loop dimensions
+* @param {Array<integer>} stridesX - loop dimension strides for the first input ndarray
+* @param {Array<integer>} stridesY - loop dimension strides for the second input ndarray
+* @param {Array<integer>} stridesZ - loop dimension strides for the output ndarray
+* @param {Object} strategyX - strategy for marshaling data to and from a first input ndarray view
+* @param {Object} strategyY - strategy for marshaling data to and from a second input ndarray view
+* @param {Object} strategyZ - strategy for marshaling data to and from an output ndarray view
+* @param {Options} opts - function options
+* @returns {void}
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+* var gwxpy = require( '@stdlib/blas/ext/base/ndarray/gwxpy' );
+*
+* // Create data buffers:
+* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+* var ybuf = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 ] );
+* var zbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+*
+* // Define the array shapes:
+* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];
+* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];
+* var zsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];
+*
+* // Define the array strides:
+* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];
+* var sy = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];
+* var sz = [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];
+*
+* // Define the index offsets:
+* var ox = 0;
+* var oy = 0;
+* var oz = 0;
+*
+* // Create the input ndarray descriptors:
+* var x = {
+*     'dtype': 'float64',
+*     'data': xbuf,
+*     'shape': xsh,
+*     'strides': sx,
+*     'offset': ox,
+*     'order': 'row-major'
+* };
+*
+* var y = {
+*     'dtype': 'float64',
+*     'data': ybuf,
+*     'shape': ysh,
+*     'strides': sy,
+*     'offset': oy,
+*     'order': 'row-major'
+* };
+*
+* // Create an output ndarray descriptor:
+* var z = {
+*     'dtype': 'float64',
+*     'data': zbuf,
+*     'shape': zsh,
+*     'strides': sz,
+*     'offset': oz,
+*     'order': 'row-major'
+* };
+*
+* // Initialize ndarray descriptors representing subarray views:
+* var views = [
+*     {
+*         'dtype': x.dtype,
+*         'data': x.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': x.offset,
+*         'order': x.order
+*     },
+*     {
+*         'dtype': y.dtype,
+*         'data': y.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': y.offset,
+*         'order': y.order
+*     },
+*     {
+*         'dtype': z.dtype,
+*         'data': z.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': z.offset,
+*         'order': z.order
+*     }
+* ];
+*
+* // Define an input strategy:
+* function inputStrategy( x ) {
+*     return {
+*         'dtype': x.dtype,
+*         'data': x.data,
+*         'shape': [ 4 ],
+*         'strides': [ 1 ],
+*         'offset': x.offset,
+*         'order': x.order
+*     };
+* }
+*
+* // Define an output strategy:
+* function outputStrategy( x ) {
+*     return x;
+* }
+*
+* var strategy = {
+*     'input': inputStrategy,
+*     'output': outputStrategy
+* };
+*
+* // Apply strided function:
+* kernel( gwxpy, [ x, y, z ], views, [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 3 ], [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], [ 12, 12, 12, 12, 12, 12, 12, 12, 12, 4 ], strategy, strategy, strategy, {} );
+*
+* var arr = ndarray2array( z.data, z.shape, z.strides, z.offset, z.order );
+* // returns [ [ [ [ [ [ [ [ [ [ [ [ 3.0, 5.0 ], [ 7.0, 9.0 ] ], [ [ 11.0, 13.0 ], [ 15.0, 17.0 ] ], [ [ 19.0, 21.0 ], [ 23.0, 25.0 ] ] ] ] ] ] ] ] ] ] ] ]
+*/
+function kernel( fcn, arrays, views, shape, stridesX, stridesY, stridesZ, strategyX, strategyY, strategyZ, opts ) { // eslint-disable-line max-params, max-statements, max-lines-per-function
+	var dv0;
+	var dv1;
+	var dv2;
+	var dv3;
+	var dv4;
+	var dv5;
+	var dv6;
+	var dv7;
+	var dv8;
+	var dv9;
+	var S0;
+	var S1;
+	var S2;
+	var S3;
+	var S4;
+	var S5;
+	var S6;
+	var S7;
+	var S8;
+	var S9;
+	var sv;
+	var iv;
+	var i0;
+	var i1;
+	var i2;
+	var i3;
+	var i4;
+	var i5;
+	var i6;
+	var i7;
+	var i8;
+	var i9;
+	var v;
+	var i;
+
+	// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...
+
+	// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...
+	if ( isRowMajor( stridesX ) ) {
+		// For row-major ndarrays, the last dimensions have the fastest changing indices...
+		S0 = shape[ 9 ];
+		S1 = shape[ 8 ];
+		S2 = shape[ 7 ];
+		S3 = shape[ 6 ];
+		S4 = shape[ 5 ];
+		S5 = shape[ 4 ];
+		S6 = shape[ 3 ];
+		S7 = shape[ 2 ];
+		S8 = shape[ 1 ];
+		S9 = shape[ 0 ];
+		dv0 = [                                   // offset increment for innermost loop
+			stridesX[9],
+			stridesY[9],
+			stridesZ[9]
+		];
+		dv1 = [
+			stridesX[8] - ( S0*stridesX[9] ),
+			stridesY[8] - ( S0*stridesY[9] ),
+			stridesZ[8] - ( S0*stridesZ[9] )
+		];
+		dv2 = [
+			stridesX[7] - ( S1*stridesX[8] ),
+			stridesY[7] - ( S1*stridesY[8] ),
+			stridesZ[7] - ( S1*stridesZ[8] )
+		];
+		dv3 = [
+			stridesX[6] - ( S2*stridesX[7] ),
+			stridesY[6] - ( S2*stridesY[7] ),
+			stridesZ[6] - ( S2*stridesZ[7] )
+		];
+		dv4 = [
+			stridesX[5] - ( S3*stridesX[6] ),
+			stridesY[5] - ( S3*stridesY[6] ),
+			stridesZ[5] - ( S3*stridesZ[6] )
+		];
+		dv5 = [
+			stridesX[4] - ( S4*stridesX[5] ),
+			stridesY[4] - ( S4*stridesY[5] ),
+			stridesZ[4] - ( S4*stridesZ[5] )
+		];
+		dv6 = [
+			stridesX[3] - ( S5*stridesX[4] ),
+			stridesY[3] - ( S5*stridesY[4] ),
+			stridesZ[3] - ( S5*stridesZ[4] )
+		];
+		dv7 = [
+			stridesX[2] - ( S6*stridesX[3] ),
+			stridesY[2] - ( S6*stridesY[3] ),
+			stridesZ[2] - ( S6*stridesZ[3] )
+		];
+		dv8 = [
+			stridesX[1] - ( S7*stridesX[2] ),
+			stridesY[1] - ( S7*stridesY[2] ),
+			stridesZ[1] - ( S7*stridesZ[2] )
+		];
+		dv9 = [                                   // offset increment for outermost loop
+			stridesX[0] - ( S8*stridesX[1] ),
+			stridesY[0] - ( S8*stridesY[1] ),
+			stridesZ[0] - ( S8*stridesZ[1] )
+		];
+		for ( i = 3; i < arrays.length; i++ ) {
+			sv = arrays[ i ].strides;
+			dv0.push( sv[9] );
+			dv1.push( sv[8] - ( S0*sv[9] ) );
+			dv2.push( sv[7] - ( S1*sv[8] ) );
+			dv3.push( sv[6] - ( S2*sv[7] ) );
+			dv4.push( sv[5] - ( S3*sv[6] ) );
+			dv5.push( sv[4] - ( S4*sv[5] ) );
+			dv6.push( sv[3] - ( S5*sv[4] ) );
+			dv7.push( sv[2] - ( S6*sv[3] ) );
+			dv8.push( sv[1] - ( S7*sv[2] ) );
+			dv9.push( sv[0] - ( S8*sv[1] ) );
+		}
+	} else { // order === 'column-major'
+		// For column-major ndarrays, the first dimensions have the fastest changing indices...
+		S0 = shape[ 0 ];
+		S1 = shape[ 1 ];
+		S2 = shape[ 2 ];
+		S3 = shape[ 3 ];
+		S4 = shape[ 4 ];
+		S5 = shape[ 5 ];
+		S6 = shape[ 6 ];
+		S7 = shape[ 7 ];
+		S8 = shape[ 8 ];
+		S9 = shape[ 9 ];
+		dv0 = [                                   // offset increment for innermost loop
+			stridesX[0],
+			stridesY[0],
+			stridesZ[0]
+		];
+		dv1 = [
+			stridesX[1] - ( S0*stridesX[0] ),
+			stridesY[1] - ( S0*stridesY[0] ),
+			stridesZ[1] - ( S0*stridesZ[0] )
+		];
+		dv2 = [
+			stridesX[2] - ( S1*stridesX[1] ),
+			stridesY[2] - ( S1*stridesY[1] ),
+			stridesZ[2] - ( S1*stridesZ[1] )
+		];
+		dv3 = [
+			stridesX[3] - ( S2*stridesX[2] ),
+			stridesY[3] - ( S2*stridesY[2] ),
+			stridesZ[3] - ( S2*stridesZ[2] )
+		];
+		dv4 = [
+			stridesX[4] - ( S3*stridesX[3] ),
+			stridesY[4] - ( S3*stridesY[3] ),
+			stridesZ[4] - ( S3*stridesZ[3] )
+		];
+		dv5 = [
+			stridesX[5] - ( S4*stridesX[4] ),
+			stridesY[5] - ( S4*stridesY[4] ),
+			stridesZ[5] - ( S4*stridesZ[4] )
+		];
+		dv6 = [
+			stridesX[6] - ( S5*stridesX[5] ),
+			stridesY[6] - ( S5*stridesY[5] ),
+			stridesZ[6] - ( S5*stridesZ[5] )
+		];
+		dv7 = [
+			stridesX[7] - ( S6*stridesX[6] ),
+			stridesY[7] - ( S6*stridesY[6] ),
+			stridesZ[7] - ( S6*stridesZ[6] )
+		];
+		dv8 = [
+			stridesX[8] - ( S7*stridesX[7] ),
+			stridesY[8] - ( S7*stridesY[7] ),
+			stridesZ[8] - ( S7*stridesZ[7] )
+		];
+		dv9 = [                                   // offset increment for outermost loop
+			stridesX[9] - ( S8*stridesX[8] ),
+			stridesY[9] - ( S8*stridesY[8] ),
+			stridesZ[9] - ( S8*stridesZ[8] )
+		];
+		for ( i = 3; i < arrays.length; i++ ) {
+			sv = arrays[ i ].strides;
+			dv0.push( sv[0] );
+			dv1.push( sv[1] - ( S0*sv[0] ) );
+			dv2.push( sv[2] - ( S1*sv[1] ) );
+			dv3.push( sv[3] - ( S2*sv[2] ) );
+			dv4.push( sv[4] - ( S3*sv[3] ) );
+			dv5.push( sv[5] - ( S4*sv[4] ) );
+			dv6.push( sv[6] - ( S5*sv[5] ) );
+			dv7.push( sv[7] - ( S6*sv[6] ) );
+			dv8.push( sv[8] - ( S7*sv[7] ) );
+			dv9.push( sv[9] - ( S8*sv[8] ) );
+		}
+	}
+	// Resolve a list of pointers to the first indexed elements in the respective ndarrays:
+	iv = offsets( arrays );
+
+	// Shallow copy the list of views to an internal array so that we can update with reshaped views without impacting the original list of views:
+	v = copyIndexed( views );
+
+	// Iterate over the loop dimensions...
+	for ( i9 = 0; i9 < S9; i9++ ) {
+		for ( i8 = 0; i8 < S8; i8++ ) {
+			for ( i7 = 0; i7 < S7; i7++ ) {
+				for ( i6 = 0; i6 < S6; i6++ ) {
+					for ( i5 = 0; i5 < S5; i5++ ) {
+						for ( i4 = 0; i4 < S4; i4++ ) {
+							for ( i3 = 0; i3 < S3; i3++ ) {
+								for ( i2 = 0; i2 < S2; i2++ ) {
+									for ( i1 = 0; i1 < S1; i1++ ) {
+										for ( i0 = 0; i0 < S0; i0++ ) {
+											setViewOffsets( views, iv );
+											v[ 0 ] = strategyX.input( views[ 0 ] );
+											v[ 1 ] = strategyY.input( views[ 1 ] );
+											v[ 2 ] = strategyZ.input( views[ 2 ] );
+											fcn( v, opts );
+											strategyZ.output( views[ 2 ] );
+											incrementOffsets( iv, dv0 );
+										}
+										incrementOffsets( iv, dv1 );
+									}
+									incrementOffsets( iv, dv2 );
+								}
+								incrementOffsets( iv, dv3 );
+							}
+							incrementOffsets( iv, dv4 );
+						}
+						incrementOffsets( iv, dv5 );
+					}
+					incrementOffsets( iv, dv6 );
+				}
+				incrementOffsets( iv, dv7 );
+			}
+			incrementOffsets( iv, dv8 );
+		}
+		incrementOffsets( iv, dv9 );
+	}
+}
+
+
+// EXPORTS //
+
+module.exports = kernel;
diff --git a/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/1d.js b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/1d.js
new file mode 100644
index 000000000000..9e6176cf1cef
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/1d.js
@@ -0,0 +1,199 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var copyIndexed = require( '@stdlib/array/base/copy-indexed' );
+var incrementOffsets = require( '@stdlib/ndarray/base/kernels/utils/increment-offsets' );
+var setViewOffsets = require( '@stdlib/ndarray/base/set-descriptor-offsets' );
+var offsets = require( '@stdlib/ndarray/base/offsets' );
+
+
+// MAIN //
+
+/**
+* Applies a one-dimensional strided array function to a list of specified dimensions in two input ndarrays and assigns results to a provided output ndarray.
+*
+* @private
+* @param {Function} fcn - wrapper for a one-dimensional strided array function
+* @param {Array<Object>} arrays - ndarray descriptors
+* @param {Array<Object>} views - initialized ndarray descriptors representing subarray views
+* @param {Array<integer>} shape - loop dimensions
+* @param {Array<integer>} stridesX - loop dimension strides for the first input ndarray
+* @param {Array<integer>} stridesY - loop dimension strides for the second input ndarray
+* @param {Array<integer>} stridesZ - loop dimension strides for the output ndarray
+* @param {Object} strategyX - strategy for marshaling data to and from a first input ndarray view
+* @param {Object} strategyY - strategy for marshaling data to and from a second input ndarray view
+* @param {Object} strategyZ - strategy for marshaling data to and from an output ndarray view
+* @param {Options} opts - function options
+* @returns {void}
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+* var gwxpy = require( '@stdlib/blas/ext/base/ndarray/gwxpy' );
+*
+* // Create data buffers:
+* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+* var ybuf = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 ] );
+* var zbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+*
+* // Define the array shapes:
+* var xsh = [ 3, 2, 2 ];
+* var ysh = [ 3, 2, 2 ];
+* var zsh = [ 3, 2, 2 ];
+*
+* // Define the array strides:
+* var sx = [ 4, 2, 1 ];
+* var sy = [ 4, 2, 1 ];
+* var sz = [ 4, 2, 1 ];
+*
+* // Define the index offsets:
+* var ox = 0;
+* var oy = 0;
+* var oz = 0;
+*
+* // Create the input ndarray descriptors:
+* var x = {
+*     'dtype': 'float64',
+*     'data': xbuf,
+*     'shape': xsh,
+*     'strides': sx,
+*     'offset': ox,
+*     'order': 'row-major'
+* };
+*
+* var y = {
+*     'dtype': 'float64',
+*     'data': ybuf,
+*     'shape': ysh,
+*     'strides': sy,
+*     'offset': oy,
+*     'order': 'row-major'
+* };
+*
+* // Create an output ndarray descriptor:
+* var z = {
+*     'dtype': 'float64',
+*     'data': zbuf,
+*     'shape': zsh,
+*     'strides': sz,
+*     'offset': oz,
+*     'order': 'row-major'
+* };
+*
+* // Initialize ndarray descriptors representing subarray views:
+* var views = [
+*     {
+*         'dtype': x.dtype,
+*         'data': x.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': x.offset,
+*         'order': x.order
+*     },
+*     {
+*         'dtype': y.dtype,
+*         'data': y.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': y.offset,
+*         'order': y.order
+*     },
+*     {
+*         'dtype': z.dtype,
+*         'data': z.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': z.offset,
+*         'order': z.order
+*     }
+* ];
+*
+* // Define an input strategy:
+* function inputStrategy( x ) {
+*     return {
+*         'dtype': x.dtype,
+*         'data': x.data,
+*         'shape': [ 4 ],
+*         'strides': [ 1 ],
+*         'offset': x.offset,
+*         'order': x.order
+*     };
+* }
+*
+* // Define an output strategy:
+* function outputStrategy( x ) {
+*     return x;
+* }
+*
+* var strategy = {
+*     'input': inputStrategy,
+*     'output': outputStrategy
+* };
+*
+* // Apply strided function:
+* kernel( gwxpy, [ x, y, z ], views, [ 3 ], [ 4 ], [ 4 ], [ 4 ], strategy, strategy, strategy, {} );
+*
+* var arr = ndarray2array( z.data, z.shape, z.strides, z.offset, z.order );
+* // returns [ [ [ 3.0, 5.0 ], [ 7.0, 9.0 ] ], [ [ 11.0, 13.0 ], [ 15.0, 17.0 ] ], [ [ 19.0, 21.0 ], [ 23.0, 25.0 ] ] ]
+*/
+function kernel( fcn, arrays, views, shape, stridesX, stridesY, stridesZ, strategyX, strategyY, strategyZ, opts ) { // eslint-disable-line max-len, max-params
+	var dv0;
+	var S0;
+	var iv;
+	var i0;
+	var v;
+	var i;
+
+	// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...
+
+	// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...
+	S0 = shape[ 0 ];
+	dv0 = [
+		stridesX[0],
+		stridesY[0],
+		stridesZ[0]
+	];
+	for ( i = 3; i < arrays.length; i++ ) {
+		dv0.push( arrays[i].strides[0] );
+	}
+	// Resolve a list of pointers to the first indexed elements in the respective ndarrays:
+	iv = offsets( arrays );
+
+	// Shallow copy the list of views to an internal array so that we can update with reshaped views without impacting the original list of views:
+	v = copyIndexed( views );
+
+	// Iterate over the loop dimensions...
+	for ( i0 = 0; i0 < S0; i0++ ) {
+		setViewOffsets( views, iv );
+		v[ 0 ] = strategyX.input( views[ 0 ] );
+		v[ 1 ] = strategyY.input( views[ 1 ] );
+		v[ 2 ] = strategyZ.input( views[ 2 ] );
+		fcn( v, opts );
+		strategyZ.output( views[ 2 ] );
+		incrementOffsets( iv, dv0 );
+	}
+}
+
+
+// EXPORTS //
+
+module.exports = kernel;
diff --git a/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/2d.js b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/2d.js
new file mode 100644
index 000000000000..7544bfc9a996
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/2d.js
@@ -0,0 +1,237 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major' );
+var copyIndexed = require( '@stdlib/array/base/copy-indexed' );
+var incrementOffsets = require( '@stdlib/ndarray/base/kernels/utils/increment-offsets' );
+var setViewOffsets = require( '@stdlib/ndarray/base/set-descriptor-offsets' );
+var offsets = require( '@stdlib/ndarray/base/offsets' );
+
+
+// MAIN //
+
+/**
+* Applies a one-dimensional strided array function to a list of specified dimensions in two input ndarrays and assigns results to a provided output ndarray.
+*
+* @private
+* @param {Function} fcn - wrapper for a one-dimensional strided array function
+* @param {Array<Object>} arrays - ndarray descriptors
+* @param {Array<Object>} views - initialized ndarray descriptors representing subarray views
+* @param {Array<integer>} shape - loop dimensions
+* @param {Array<integer>} stridesX - loop dimension strides for the first input ndarray
+* @param {Array<integer>} stridesY - loop dimension strides for the second input ndarray
+* @param {Array<integer>} stridesZ - loop dimension strides for the output ndarray
+* @param {Object} strategyX - strategy for marshaling data to and from a first input ndarray view
+* @param {Object} strategyY - strategy for marshaling data to and from a second input ndarray view
+* @param {Object} strategyZ - strategy for marshaling data to and from an output ndarray view
+* @param {Options} opts - function options
+* @returns {void}
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+* var gwxpy = require( '@stdlib/blas/ext/base/ndarray/gwxpy' );
+*
+* // Create data buffers:
+* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+* var ybuf = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 ] );
+* var zbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+*
+* // Define the array shapes:
+* var xsh = [ 1, 3, 2, 2 ];
+* var ysh = [ 1, 3, 2, 2 ];
+* var zsh = [ 1, 3, 2, 2 ];
+*
+* // Define the array strides:
+* var sx = [ 12, 4, 2, 1 ];
+* var sy = [ 12, 4, 2, 1 ];
+* var sz = [ 12, 4, 2, 1 ];
+*
+* // Define the index offsets:
+* var ox = 0;
+* var oy = 0;
+* var oz = 0;
+*
+* // Create the input ndarray descriptors:
+* var x = {
+*     'dtype': 'float64',
+*     'data': xbuf,
+*     'shape': xsh,
+*     'strides': sx,
+*     'offset': ox,
+*     'order': 'row-major'
+* };
+*
+* var y = {
+*     'dtype': 'float64',
+*     'data': ybuf,
+*     'shape': ysh,
+*     'strides': sy,
+*     'offset': oy,
+*     'order': 'row-major'
+* };
+*
+* // Create an output ndarray descriptor:
+* var z = {
+*     'dtype': 'float64',
+*     'data': zbuf,
+*     'shape': zsh,
+*     'strides': sz,
+*     'offset': oz,
+*     'order': 'row-major'
+* };
+*
+* // Initialize ndarray descriptors representing subarray views:
+* var views = [
+*     {
+*         'dtype': x.dtype,
+*         'data': x.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': x.offset,
+*         'order': x.order
+*     },
+*     {
+*         'dtype': y.dtype,
+*         'data': y.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': y.offset,
+*         'order': y.order
+*     },
+*     {
+*         'dtype': z.dtype,
+*         'data': z.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': z.offset,
+*         'order': z.order
+*     }
+* ];
+*
+* // Define an input strategy:
+* function inputStrategy( x ) {
+*     return {
+*         'dtype': x.dtype,
+*         'data': x.data,
+*         'shape': [ 4 ],
+*         'strides': [ 1 ],
+*         'offset': x.offset,
+*         'order': x.order
+*     };
+* }
+*
+* // Define an output strategy:
+* function outputStrategy( x ) {
+*     return x;
+* }
+*
+* var strategy = {
+*     'input': inputStrategy,
+*     'output': outputStrategy
+* };
+*
+* // Apply strided function:
+* kernel( gwxpy, [ x, y, z ], views, [ 1, 3 ], [ 12, 4 ], [ 12, 4 ], [ 12, 4 ], strategy, strategy, strategy, {} );
+*
+* var arr = ndarray2array( z.data, z.shape, z.strides, z.offset, z.order );
+* // returns [ [ [ [ 3.0, 5.0 ], [ 7.0, 9.0 ] ], [ [ 11.0, 13.0 ], [ 15.0, 17.0 ] ], [ [ 19.0, 21.0 ], [ 23.0, 25.0 ] ] ] ]
+*/
+function kernel( fcn, arrays, views, shape, stridesX, stridesY, stridesZ, strategyX, strategyY, strategyZ, opts ) { // eslint-disable-line max-len, max-params
+	var dv0;
+	var dv1;
+	var S0;
+	var S1;
+	var sv;
+	var iv;
+	var i0;
+	var i1;
+	var v;
+	var i;
+
+	// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...
+
+	// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...
+	if ( isRowMajor( stridesX ) ) {
+		// For row-major ndarrays, the last dimensions have the fastest changing indices...
+		S0 = shape[ 1 ];
+		S1 = shape[ 0 ];
+		dv0 = [                                   // offset increment for innermost loop
+			stridesX[1],
+			stridesY[1],
+			stridesZ[1]
+		];
+		dv1 = [                                   // offset increment for outermost loop
+			stridesX[0] - ( S0*stridesX[1] ),
+			stridesY[0] - ( S0*stridesY[1] ),
+			stridesZ[0] - ( S0*stridesZ[1] )
+		];
+		for ( i = 3; i < arrays.length; i++ ) {
+			sv = arrays[ i ].strides;
+			dv0.push( sv[1] );
+			dv1.push( sv[0] - ( S0*sv[1] ) );
+		}
+	} else { // order === 'column-major'
+		// For column-major ndarrays, the first dimensions have the fastest changing indices...
+		S0 = shape[ 0 ];
+		S1 = shape[ 1 ];
+		dv0 = [                                   // offset increment for innermost loop
+			stridesX[0],
+			stridesY[0],
+			stridesZ[0]
+		];
+		dv1 = [                                   // offset increment for outermost loop
+			stridesX[1] - ( S0*stridesX[0] ),
+			stridesY[1] - ( S0*stridesY[0] ),
+			stridesZ[1] - ( S0*stridesZ[0] )
+		];
+		for ( i = 3; i < arrays.length; i++ ) {
+			sv = arrays[ i ].strides;
+			dv0.push( sv[0] );
+			dv1.push( sv[1] - ( S0*sv[0] ) );
+		}
+	}
+	// Resolve a list of pointers to the first indexed elements in the respective ndarrays:
+	iv = offsets( arrays );
+
+	// Shallow copy the list of views to an internal array so that we can update with reshaped views without impacting the original list of views:
+	v = copyIndexed( views );
+
+	// Iterate over the loop dimensions...
+	for ( i1 = 0; i1 < S1; i1++ ) {
+		for ( i0 = 0; i0 < S0; i0++ ) {
+			setViewOffsets( views, iv );
+			v[ 0 ] = strategyX.input( views[ 0 ] );
+			v[ 1 ] = strategyY.input( views[ 1 ] );
+			v[ 2 ] = strategyZ.input( views[ 2 ] );
+			fcn( v, opts );
+			strategyZ.output( views[ 2 ] );
+			incrementOffsets( iv, dv0 );
+		}
+		incrementOffsets( iv, dv1 );
+	}
+}
+
+
+// EXPORTS //
+
+module.exports = kernel;
diff --git a/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/3d.js b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/3d.js
new file mode 100644
index 000000000000..bb7eb0c243a7
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/3d.js
@@ -0,0 +1,257 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major' );
+var copyIndexed = require( '@stdlib/array/base/copy-indexed' );
+var incrementOffsets = require( '@stdlib/ndarray/base/kernels/utils/increment-offsets' );
+var setViewOffsets = require( '@stdlib/ndarray/base/set-descriptor-offsets' );
+var offsets = require( '@stdlib/ndarray/base/offsets' );
+
+
+// MAIN //
+
+/**
+* Applies a one-dimensional strided array function to a list of specified dimensions in two input ndarrays and assigns results to a provided output ndarray.
+*
+* @private
+* @param {Function} fcn - wrapper for a one-dimensional strided array function
+* @param {Array<Object>} arrays - ndarray descriptors
+* @param {Array<Object>} views - initialized ndarray descriptors representing subarray views
+* @param {Array<integer>} shape - loop dimensions
+* @param {Array<integer>} stridesX - loop dimension strides for the first input ndarray
+* @param {Array<integer>} stridesY - loop dimension strides for the second input ndarray
+* @param {Array<integer>} stridesZ - loop dimension strides for the output ndarray
+* @param {Object} strategyX - strategy for marshaling data to and from a first input ndarray view
+* @param {Object} strategyY - strategy for marshaling data to and from a second input ndarray view
+* @param {Object} strategyZ - strategy for marshaling data to and from an output ndarray view
+* @param {Options} opts - function options
+* @returns {void}
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+* var gwxpy = require( '@stdlib/blas/ext/base/ndarray/gwxpy' );
+*
+* // Create data buffers:
+* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+* var ybuf = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 ] );
+* var zbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+*
+* // Define the array shapes:
+* var xsh = [ 1, 1, 3, 2, 2 ];
+* var ysh = [ 1, 1, 3, 2, 2 ];
+* var zsh = [ 1, 1, 3, 2, 2 ];
+*
+* // Define the array strides:
+* var sx = [ 12, 12, 4, 2, 1 ];
+* var sy = [ 12, 12, 4, 2, 1 ];
+* var sz = [ 12, 12, 4, 2, 1 ];
+*
+* // Define the index offsets:
+* var ox = 0;
+* var oy = 0;
+* var oz = 0;
+*
+* // Create the input ndarray descriptors:
+* var x = {
+*     'dtype': 'float64',
+*     'data': xbuf,
+*     'shape': xsh,
+*     'strides': sx,
+*     'offset': ox,
+*     'order': 'row-major'
+* };
+*
+* var y = {
+*     'dtype': 'float64',
+*     'data': ybuf,
+*     'shape': ysh,
+*     'strides': sy,
+*     'offset': oy,
+*     'order': 'row-major'
+* };
+*
+* // Create an output ndarray descriptor:
+* var z = {
+*     'dtype': 'float64',
+*     'data': zbuf,
+*     'shape': zsh,
+*     'strides': sz,
+*     'offset': oz,
+*     'order': 'row-major'
+* };
+*
+* // Initialize ndarray descriptors representing subarray views:
+* var views = [
+*     {
+*         'dtype': x.dtype,
+*         'data': x.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': x.offset,
+*         'order': x.order
+*     },
+*     {
+*         'dtype': y.dtype,
+*         'data': y.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': y.offset,
+*         'order': y.order
+*     },
+*     {
+*         'dtype': z.dtype,
+*         'data': z.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': z.offset,
+*         'order': z.order
+*     }
+* ];
+*
+* // Define an input strategy:
+* function inputStrategy( x ) {
+*     return {
+*         'dtype': x.dtype,
+*         'data': x.data,
+*         'shape': [ 4 ],
+*         'strides': [ 1 ],
+*         'offset': x.offset,
+*         'order': x.order
+*     };
+* }
+*
+* // Define an output strategy:
+* function outputStrategy( x ) {
+*     return x;
+* }
+*
+* var strategy = {
+*     'input': inputStrategy,
+*     'output': outputStrategy
+* };
+*
+* // Apply strided function:
+* kernel( gwxpy, [ x, y, z ], views, [ 1, 1, 3 ], [ 12, 12, 4 ], [ 12, 12, 4 ], [ 12, 12, 4 ], strategy, strategy, strategy, {} );
+*
+* var arr = ndarray2array( z.data, z.shape, z.strides, z.offset, z.order );
+* // returns [ [ [ [ [ 3.0, 5.0 ], [ 7.0, 9.0 ] ], [ [ 11.0, 13.0 ], [ 15.0, 17.0 ] ], [ [ 19.0, 21.0 ], [ 23.0, 25.0 ] ] ] ] ]
+*/
+function kernel( fcn, arrays, views, shape, stridesX, stridesY, stridesZ, strategyX, strategyY, strategyZ, opts ) { // eslint-disable-line max-len, max-params
+	var dv0;
+	var dv1;
+	var dv2;
+	var S0;
+	var S1;
+	var S2;
+	var sv;
+	var iv;
+	var i0;
+	var i1;
+	var i2;
+	var v;
+	var i;
+
+	// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...
+
+	// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...
+	if ( isRowMajor( stridesX ) ) {
+		// For row-major ndarrays, the last dimensions have the fastest changing indices...
+		S0 = shape[ 2 ];
+		S1 = shape[ 1 ];
+		S2 = shape[ 0 ];
+		dv0 = [                                   // offset increment for innermost loop
+			stridesX[2],
+			stridesY[2],
+			stridesZ[2]
+		];
+		dv1 = [
+			stridesX[1] - ( S0*stridesX[2] ),
+			stridesY[1] - ( S0*stridesY[2] ),
+			stridesZ[1] - ( S0*stridesZ[2] )
+		];
+		dv2 = [                                   // offset increment for outermost loop
+			stridesX[0] - ( S1*stridesX[1] ),
+			stridesY[0] - ( S1*stridesY[1] ),
+			stridesZ[0] - ( S1*stridesZ[1] )
+		];
+		for ( i = 3; i < arrays.length; i++ ) {
+			sv = arrays[ i ].strides;
+			dv0.push( sv[2] );
+			dv1.push( sv[1] - ( S0*sv[2] ) );
+			dv2.push( sv[0] - ( S1*sv[1] ) );
+		}
+	} else { // order === 'column-major'
+		// For column-major ndarrays, the first dimensions have the fastest changing indices...
+		S0 = shape[ 0 ];
+		S1 = shape[ 1 ];
+		S2 = shape[ 2 ];
+		dv0 = [                                   // offset increment for innermost loop
+			stridesX[0],
+			stridesY[0],
+			stridesZ[0]
+		];
+		dv1 = [
+			stridesX[1] - ( S0*stridesX[0] ),
+			stridesY[1] - ( S0*stridesY[0] ),
+			stridesZ[1] - ( S0*stridesZ[0] )
+		];
+		dv2 = [                                   // offset increment for outermost loop
+			stridesX[2] - ( S1*stridesX[1] ),
+			stridesY[2] - ( S1*stridesY[1] ),
+			stridesZ[2] - ( S1*stridesZ[1] )
+		];
+		for ( i = 3; i < arrays.length; i++ ) {
+			sv = arrays[ i ].strides;
+			dv0.push( sv[0] );
+			dv1.push( sv[1] - ( S0*sv[0] ) );
+			dv2.push( sv[2] - ( S1*sv[1] ) );
+		}
+	}
+	// Resolve a list of pointers to the first indexed elements in the respective ndarrays:
+	iv = offsets( arrays );
+
+	// Shallow copy the list of views to an internal array so that we can update with reshaped views without impacting the original list of views:
+	v = copyIndexed( views );
+
+	// Iterate over the loop dimensions...
+	for ( i2 = 0; i2 < S2; i2++ ) {
+		for ( i1 = 0; i1 < S1; i1++ ) {
+			for ( i0 = 0; i0 < S0; i0++ ) {
+				setViewOffsets( views, iv );
+				v[ 0 ] = strategyX.input( views[ 0 ] );
+				v[ 1 ] = strategyY.input( views[ 1 ] );
+				v[ 2 ] = strategyZ.input( views[ 2 ] );
+				fcn( v, opts );
+				strategyZ.output( views[ 2 ] );
+				incrementOffsets( iv, dv0 );
+			}
+			incrementOffsets( iv, dv1 );
+		}
+		incrementOffsets( iv, dv2 );
+	}
+}
+
+
+// EXPORTS //
+
+module.exports = kernel;
diff --git a/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/4d.js b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/4d.js
new file mode 100644
index 000000000000..269d0c254bd0
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/4d.js
@@ -0,0 +1,277 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major' );
+var copyIndexed = require( '@stdlib/array/base/copy-indexed' );
+var incrementOffsets = require( '@stdlib/ndarray/base/kernels/utils/increment-offsets' );
+var setViewOffsets = require( '@stdlib/ndarray/base/set-descriptor-offsets' );
+var offsets = require( '@stdlib/ndarray/base/offsets' );
+
+
+// MAIN //
+
+/**
+* Applies a one-dimensional strided array function to a list of specified dimensions in two input ndarrays and assigns results to a provided output ndarray.
+*
+* @private
+* @param {Function} fcn - wrapper for a one-dimensional strided array function
+* @param {Array<Object>} arrays - ndarray descriptors
+* @param {Array<Object>} views - initialized ndarray descriptors representing subarray views
+* @param {Array<integer>} shape - loop dimensions
+* @param {Array<integer>} stridesX - loop dimension strides for the first input ndarray
+* @param {Array<integer>} stridesY - loop dimension strides for the second input ndarray
+* @param {Array<integer>} stridesZ - loop dimension strides for the output ndarray
+* @param {Object} strategyX - strategy for marshaling data to and from a first input ndarray view
+* @param {Object} strategyY - strategy for marshaling data to and from a second input ndarray view
+* @param {Object} strategyZ - strategy for marshaling data to and from an output ndarray view
+* @param {Options} opts - function options
+* @returns {void}
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+* var gwxpy = require( '@stdlib/blas/ext/base/ndarray/gwxpy' );
+*
+* // Create data buffers:
+* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+* var ybuf = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 ] );
+* var zbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+*
+* // Define the array shapes:
+* var xsh = [ 1, 1, 1, 3, 2, 2 ];
+* var ysh = [ 1, 1, 1, 3, 2, 2 ];
+* var zsh = [ 1, 1, 1, 3, 2, 2 ];
+*
+* // Define the array strides:
+* var sx = [ 12, 12, 12, 4, 2, 1 ];
+* var sy = [ 12, 12, 12, 4, 2, 1 ];
+* var sz = [ 12, 12, 12, 4, 2, 1 ];
+*
+* // Define the index offsets:
+* var ox = 0;
+* var oy = 0;
+* var oz = 0;
+*
+* // Create the input ndarray descriptors:
+* var x = {
+*     'dtype': 'float64',
+*     'data': xbuf,
+*     'shape': xsh,
+*     'strides': sx,
+*     'offset': ox,
+*     'order': 'row-major'
+* };
+*
+* var y = {
+*     'dtype': 'float64',
+*     'data': ybuf,
+*     'shape': ysh,
+*     'strides': sy,
+*     'offset': oy,
+*     'order': 'row-major'
+* };
+*
+* // Create an output ndarray descriptor:
+* var z = {
+*     'dtype': 'float64',
+*     'data': zbuf,
+*     'shape': zsh,
+*     'strides': sz,
+*     'offset': oz,
+*     'order': 'row-major'
+* };
+*
+* // Initialize ndarray descriptors representing subarray views:
+* var views = [
+*     {
+*         'dtype': x.dtype,
+*         'data': x.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': x.offset,
+*         'order': x.order
+*     },
+*     {
+*         'dtype': y.dtype,
+*         'data': y.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': y.offset,
+*         'order': y.order
+*     },
+*     {
+*         'dtype': z.dtype,
+*         'data': z.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': z.offset,
+*         'order': z.order
+*     }
+* ];
+*
+* // Define an input strategy:
+* function inputStrategy( x ) {
+*     return {
+*         'dtype': x.dtype,
+*         'data': x.data,
+*         'shape': [ 4 ],
+*         'strides': [ 1 ],
+*         'offset': x.offset,
+*         'order': x.order
+*     };
+* }
+*
+* // Define an output strategy:
+* function outputStrategy( x ) {
+*     return x;
+* }
+*
+* var strategy = {
+*     'input': inputStrategy,
+*     'output': outputStrategy
+* };
+*
+* // Apply strided function:
+* kernel( gwxpy, [ x, y, z ], views, [ 1, 1, 1, 3 ], [ 12, 12, 12, 4 ], [ 12, 12, 12, 4 ], [ 12, 12, 12, 4 ], strategy, strategy, strategy, {} );
+*
+* var arr = ndarray2array( z.data, z.shape, z.strides, z.offset, z.order );
+* // returns [ [ [ [ [ [ 3.0, 5.0 ], [ 7.0, 9.0 ] ], [ [ 11.0, 13.0 ], [ 15.0, 17.0 ] ], [ [ 19.0, 21.0 ], [ 23.0, 25.0 ] ] ] ] ] ]
+*/
+function kernel( fcn, arrays, views, shape, stridesX, stridesY, stridesZ, strategyX, strategyY, strategyZ, opts ) { // eslint-disable-line max-len, max-params
+	var dv0;
+	var dv1;
+	var dv2;
+	var dv3;
+	var S0;
+	var S1;
+	var S2;
+	var S3;
+	var sv;
+	var iv;
+	var i0;
+	var i1;
+	var i2;
+	var i3;
+	var v;
+	var i;
+
+	// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...
+
+	// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...
+	if ( isRowMajor( stridesX ) ) {
+		// For row-major ndarrays, the last dimensions have the fastest changing indices...
+		S0 = shape[ 3 ];
+		S1 = shape[ 2 ];
+		S2 = shape[ 1 ];
+		S3 = shape[ 0 ];
+		dv0 = [                                   // offset increment for innermost loop
+			stridesX[3],
+			stridesY[3],
+			stridesZ[3]
+		];
+		dv1 = [
+			stridesX[2] - ( S0*stridesX[3] ),
+			stridesY[2] - ( S0*stridesY[3] ),
+			stridesZ[2] - ( S0*stridesZ[3] )
+		];
+		dv2 = [
+			stridesX[1] - ( S1*stridesX[2] ),
+			stridesY[1] - ( S1*stridesY[2] ),
+			stridesZ[1] - ( S1*stridesZ[2] )
+		];
+		dv3 = [                                   // offset increment for outermost loop
+			stridesX[0] - ( S2*stridesX[1] ),
+			stridesY[0] - ( S2*stridesY[1] ),
+			stridesZ[0] - ( S2*stridesZ[1] )
+		];
+		for ( i = 3; i < arrays.length; i++ ) {
+			sv = arrays[ i ].strides;
+			dv0.push( sv[3] );
+			dv1.push( sv[2] - ( S0*sv[3] ) );
+			dv2.push( sv[1] - ( S1*sv[2] ) );
+			dv3.push( sv[0] - ( S2*sv[1] ) );
+		}
+	} else { // order === 'column-major'
+		// For column-major ndarrays, the first dimensions have the fastest changing indices...
+		S0 = shape[ 0 ];
+		S1 = shape[ 1 ];
+		S2 = shape[ 2 ];
+		S3 = shape[ 3 ];
+		dv0 = [                                   // offset increment for innermost loop
+			stridesX[0],
+			stridesY[0],
+			stridesZ[0]
+		];
+		dv1 = [
+			stridesX[1] - ( S0*stridesX[0] ),
+			stridesY[1] - ( S0*stridesY[0] ),
+			stridesZ[1] - ( S0*stridesZ[0] )
+		];
+		dv2 = [
+			stridesX[2] - ( S1*stridesX[1] ),
+			stridesY[2] - ( S1*stridesY[1] ),
+			stridesZ[2] - ( S1*stridesZ[1] )
+		];
+		dv3 = [                                   // offset increment for outermost loop
+			stridesX[3] - ( S2*stridesX[2] ),
+			stridesY[3] - ( S2*stridesY[2] ),
+			stridesZ[3] - ( S2*stridesZ[2] )
+		];
+		for ( i = 3; i < arrays.length; i++ ) {
+			sv = arrays[ i ].strides;
+			dv0.push( sv[0] );
+			dv1.push( sv[1] - ( S0*sv[0] ) );
+			dv2.push( sv[2] - ( S1*sv[1] ) );
+			dv3.push( sv[3] - ( S2*sv[2] ) );
+		}
+	}
+	// Resolve a list of pointers to the first indexed elements in the respective ndarrays:
+	iv = offsets( arrays );
+
+	// Shallow copy the list of views to an internal array so that we can update with reshaped views without impacting the original list of views:
+	v = copyIndexed( views );
+
+	// Iterate over the loop dimensions...
+	for ( i3 = 0; i3 < S3; i3++ ) {
+		for ( i2 = 0; i2 < S2; i2++ ) {
+			for ( i1 = 0; i1 < S1; i1++ ) {
+				for ( i0 = 0; i0 < S0; i0++ ) {
+					setViewOffsets( views, iv );
+					v[ 0 ] = strategyX.input( views[ 0 ] );
+					v[ 1 ] = strategyY.input( views[ 1 ] );
+					v[ 2 ] = strategyZ.input( views[ 2 ] );
+					fcn( v, opts );
+					strategyZ.output( views[ 2 ] );
+					incrementOffsets( iv, dv0 );
+				}
+				incrementOffsets( iv, dv1 );
+			}
+			incrementOffsets( iv, dv2 );
+		}
+		incrementOffsets( iv, dv3 );
+	}
+}
+
+
+// EXPORTS //
+
+module.exports = kernel;
diff --git a/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/5d.js b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/5d.js
new file mode 100644
index 000000000000..423f0f3d8048
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/5d.js
@@ -0,0 +1,297 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major' );
+var copyIndexed = require( '@stdlib/array/base/copy-indexed' );
+var incrementOffsets = require( '@stdlib/ndarray/base/kernels/utils/increment-offsets' );
+var setViewOffsets = require( '@stdlib/ndarray/base/set-descriptor-offsets' );
+var offsets = require( '@stdlib/ndarray/base/offsets' );
+
+
+// MAIN //
+
+/**
+* Applies a one-dimensional strided array function to a list of specified dimensions in two input ndarrays and assigns results to a provided output ndarray.
+*
+* @private
+* @param {Function} fcn - wrapper for a one-dimensional strided array function
+* @param {Array<Object>} arrays - ndarray descriptors
+* @param {Array<Object>} views - initialized ndarray descriptors representing subarray views
+* @param {Array<integer>} shape - loop dimensions
+* @param {Array<integer>} stridesX - loop dimension strides for the first input ndarray
+* @param {Array<integer>} stridesY - loop dimension strides for the second input ndarray
+* @param {Array<integer>} stridesZ - loop dimension strides for the output ndarray
+* @param {Object} strategyX - strategy for marshaling data to and from a first input ndarray view
+* @param {Object} strategyY - strategy for marshaling data to and from a second input ndarray view
+* @param {Object} strategyZ - strategy for marshaling data to and from an output ndarray view
+* @param {Options} opts - function options
+* @returns {void}
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+* var gwxpy = require( '@stdlib/blas/ext/base/ndarray/gwxpy' );
+*
+* // Create data buffers:
+* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+* var ybuf = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 ] );
+* var zbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+*
+* // Define the array shapes:
+* var xsh = [ 1, 1, 1, 1, 3, 2, 2 ];
+* var ysh = [ 1, 1, 1, 1, 3, 2, 2 ];
+* var zsh = [ 1, 1, 1, 1, 3, 2, 2 ];
+*
+* // Define the array strides:
+* var sx = [ 12, 12, 12, 12, 4, 2, 1 ];
+* var sy = [ 12, 12, 12, 12, 4, 2, 1 ];
+* var sz = [ 12, 12, 12, 12, 4, 2, 1 ];
+*
+* // Define the index offsets:
+* var ox = 0;
+* var oy = 0;
+* var oz = 0;
+*
+* // Create the input ndarray descriptors:
+* var x = {
+*     'dtype': 'float64',
+*     'data': xbuf,
+*     'shape': xsh,
+*     'strides': sx,
+*     'offset': ox,
+*     'order': 'row-major'
+* };
+*
+* var y = {
+*     'dtype': 'float64',
+*     'data': ybuf,
+*     'shape': ysh,
+*     'strides': sy,
+*     'offset': oy,
+*     'order': 'row-major'
+* };
+*
+* // Create an output ndarray descriptor:
+* var z = {
+*     'dtype': 'float64',
+*     'data': zbuf,
+*     'shape': zsh,
+*     'strides': sz,
+*     'offset': oz,
+*     'order': 'row-major'
+* };
+*
+* // Initialize ndarray descriptors representing subarray views:
+* var views = [
+*     {
+*         'dtype': x.dtype,
+*         'data': x.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': x.offset,
+*         'order': x.order
+*     },
+*     {
+*         'dtype': y.dtype,
+*         'data': y.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': y.offset,
+*         'order': y.order
+*     },
+*     {
+*         'dtype': z.dtype,
+*         'data': z.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': z.offset,
+*         'order': z.order
+*     }
+* ];
+*
+* // Define an input strategy:
+* function inputStrategy( x ) {
+*     return {
+*         'dtype': x.dtype,
+*         'data': x.data,
+*         'shape': [ 4 ],
+*         'strides': [ 1 ],
+*         'offset': x.offset,
+*         'order': x.order
+*     };
+* }
+*
+* // Define an output strategy:
+* function outputStrategy( x ) {
+*     return x;
+* }
+*
+* var strategy = {
+*     'input': inputStrategy,
+*     'output': outputStrategy
+* };
+*
+* // Apply strided function:
+* kernel( gwxpy, [ x, y, z ], views, [ 1, 1, 1, 1, 3 ], [ 12, 12, 12, 12, 4 ], [ 12, 12, 12, 12, 4 ], [ 12, 12, 12, 12, 4 ], strategy, strategy, strategy, {} );
+*
+* var arr = ndarray2array( z.data, z.shape, z.strides, z.offset, z.order );
+* // returns [ [ [ [ [ [ [ 3.0, 5.0 ], [ 7.0, 9.0 ] ], [ [ 11.0, 13.0 ], [ 15.0, 17.0 ] ], [ [ 19.0, 21.0 ], [ 23.0, 25.0 ] ] ] ] ] ] ]
+*/
+function kernel( fcn, arrays, views, shape, stridesX, stridesY, stridesZ, strategyX, strategyY, strategyZ, opts ) { // eslint-disable-line max-len, max-params
+	var dv0;
+	var dv1;
+	var dv2;
+	var dv3;
+	var dv4;
+	var S0;
+	var S1;
+	var S2;
+	var S3;
+	var S4;
+	var sv;
+	var iv;
+	var i0;
+	var i1;
+	var i2;
+	var i3;
+	var i4;
+	var v;
+	var i;
+
+	// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...
+
+	// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...
+	if ( isRowMajor( stridesX ) ) {
+		// For row-major ndarrays, the last dimensions have the fastest changing indices...
+		S0 = shape[ 4 ];
+		S1 = shape[ 3 ];
+		S2 = shape[ 2 ];
+		S3 = shape[ 1 ];
+		S4 = shape[ 0 ];
+		dv0 = [                                   // offset increment for innermost loop
+			stridesX[4],
+			stridesY[4],
+			stridesZ[4]
+		];
+		dv1 = [
+			stridesX[3] - ( S0*stridesX[4] ),
+			stridesY[3] - ( S0*stridesY[4] ),
+			stridesZ[3] - ( S0*stridesZ[4] )
+		];
+		dv2 = [
+			stridesX[2] - ( S1*stridesX[3] ),
+			stridesY[2] - ( S1*stridesY[3] ),
+			stridesZ[2] - ( S1*stridesZ[3] )
+		];
+		dv3 = [
+			stridesX[1] - ( S2*stridesX[2] ),
+			stridesY[1] - ( S2*stridesY[2] ),
+			stridesZ[1] - ( S2*stridesZ[2] )
+		];
+		dv4 = [                                   // offset increment for outermost loop
+			stridesX[0] - ( S3*stridesX[1] ),
+			stridesY[0] - ( S3*stridesY[1] ),
+			stridesZ[0] - ( S3*stridesZ[1] )
+		];
+		for ( i = 3; i < arrays.length; i++ ) {
+			sv = arrays[ i ].strides;
+			dv0.push( sv[4] );
+			dv1.push( sv[3] - ( S0*sv[4] ) );
+			dv2.push( sv[2] - ( S1*sv[3] ) );
+			dv3.push( sv[1] - ( S2*sv[2] ) );
+			dv4.push( sv[0] - ( S3*sv[1] ) );
+		}
+	} else { // order === 'column-major'
+		// For column-major ndarrays, the first dimensions have the fastest changing indices...
+		S0 = shape[ 0 ];
+		S1 = shape[ 1 ];
+		S2 = shape[ 2 ];
+		S3 = shape[ 3 ];
+		S4 = shape[ 4 ];
+		dv0 = [                                   // offset increment for innermost loop
+			stridesX[0],
+			stridesY[0],
+			stridesZ[0]
+		];
+		dv1 = [
+			stridesX[1] - ( S0*stridesX[0] ),
+			stridesY[1] - ( S0*stridesY[0] ),
+			stridesZ[1] - ( S0*stridesZ[0] )
+		];
+		dv2 = [
+			stridesX[2] - ( S1*stridesX[1] ),
+			stridesY[2] - ( S1*stridesY[1] ),
+			stridesZ[2] - ( S1*stridesZ[1] )
+		];
+		dv3 = [
+			stridesX[3] - ( S2*stridesX[2] ),
+			stridesY[3] - ( S2*stridesY[2] ),
+			stridesZ[3] - ( S2*stridesZ[2] )
+		];
+		dv4 = [                                   // offset increment for outermost loop
+			stridesX[4] - ( S3*stridesX[3] ),
+			stridesY[4] - ( S3*stridesY[3] ),
+			stridesZ[4] - ( S3*stridesZ[3] )
+		];
+		for ( i = 3; i < arrays.length; i++ ) {
+			sv = arrays[ i ].strides;
+			dv0.push( sv[0] );
+			dv1.push( sv[1] - ( S0*sv[0] ) );
+			dv2.push( sv[2] - ( S1*sv[1] ) );
+			dv3.push( sv[3] - ( S2*sv[2] ) );
+			dv4.push( sv[4] - ( S3*sv[3] ) );
+		}
+	}
+	// Resolve a list of pointers to the first indexed elements in the respective ndarrays:
+	iv = offsets( arrays );
+
+	// Shallow copy the list of views to an internal array so that we can update with reshaped views without impacting the original list of views:
+	v = copyIndexed( views );
+
+	// Iterate over the loop dimensions...
+	for ( i4 = 0; i4 < S4; i4++ ) {
+		for ( i3 = 0; i3 < S3; i3++ ) {
+			for ( i2 = 0; i2 < S2; i2++ ) {
+				for ( i1 = 0; i1 < S1; i1++ ) {
+					for ( i0 = 0; i0 < S0; i0++ ) {
+						setViewOffsets( views, iv );
+						v[ 0 ] = strategyX.input( views[ 0 ] );
+						v[ 1 ] = strategyY.input( views[ 1 ] );
+						v[ 2 ] = strategyZ.input( views[ 2 ] );
+						fcn( v, opts );
+						strategyZ.output( views[ 2 ] );
+						incrementOffsets( iv, dv0 );
+					}
+					incrementOffsets( iv, dv1 );
+				}
+				incrementOffsets( iv, dv2 );
+			}
+			incrementOffsets( iv, dv3 );
+		}
+		incrementOffsets( iv, dv4 );
+	}
+}
+
+
+// EXPORTS //
+
+module.exports = kernel;
diff --git a/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/6d.js b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/6d.js
new file mode 100644
index 000000000000..2e52f94de4c9
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/6d.js
@@ -0,0 +1,319 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/* eslint-disable max-depth */
+
+'use strict';
+
+// MODULES //
+
+var isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major' );
+var copyIndexed = require( '@stdlib/array/base/copy-indexed' );
+var incrementOffsets = require( '@stdlib/ndarray/base/kernels/utils/increment-offsets' );
+var setViewOffsets = require( '@stdlib/ndarray/base/set-descriptor-offsets' );
+var offsets = require( '@stdlib/ndarray/base/offsets' );
+
+
+// MAIN //
+
+/**
+* Applies a one-dimensional strided array function to a list of specified dimensions in two input ndarrays and assigns results to a provided output ndarray.
+*
+* @private
+* @param {Function} fcn - wrapper for a one-dimensional strided array function
+* @param {Array<Object>} arrays - ndarray descriptors
+* @param {Array<Object>} views - initialized ndarray descriptors representing subarray views
+* @param {Array<integer>} shape - loop dimensions
+* @param {Array<integer>} stridesX - loop dimension strides for the first input ndarray
+* @param {Array<integer>} stridesY - loop dimension strides for the second input ndarray
+* @param {Array<integer>} stridesZ - loop dimension strides for the output ndarray
+* @param {Object} strategyX - strategy for marshaling data to and from a first input ndarray view
+* @param {Object} strategyY - strategy for marshaling data to and from a second input ndarray view
+* @param {Object} strategyZ - strategy for marshaling data to and from an output ndarray view
+* @param {Options} opts - function options
+* @returns {void}
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+* var gwxpy = require( '@stdlib/blas/ext/base/ndarray/gwxpy' );
+*
+* // Create data buffers:
+* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+* var ybuf = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 ] );
+* var zbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+*
+* // Define the array shapes:
+* var xsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];
+* var ysh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];
+* var zsh = [ 1, 1, 1, 1, 1, 3, 2, 2 ];
+*
+* // Define the array strides:
+* var sx = [ 12, 12, 12, 12, 12, 4, 2, 1 ];
+* var sy = [ 12, 12, 12, 12, 12, 4, 2, 1 ];
+* var sz = [ 12, 12, 12, 12, 12, 4, 2, 1 ];
+*
+* // Define the index offsets:
+* var ox = 0;
+* var oy = 0;
+* var oz = 0;
+*
+* // Create the input ndarray descriptors:
+* var x = {
+*     'dtype': 'float64',
+*     'data': xbuf,
+*     'shape': xsh,
+*     'strides': sx,
+*     'offset': ox,
+*     'order': 'row-major'
+* };
+*
+* var y = {
+*     'dtype': 'float64',
+*     'data': ybuf,
+*     'shape': ysh,
+*     'strides': sy,
+*     'offset': oy,
+*     'order': 'row-major'
+* };
+*
+* // Create an output ndarray descriptor:
+* var z = {
+*     'dtype': 'float64',
+*     'data': zbuf,
+*     'shape': zsh,
+*     'strides': sz,
+*     'offset': oz,
+*     'order': 'row-major'
+* };
+*
+* // Initialize ndarray descriptors representing subarray views:
+* var views = [
+*     {
+*         'dtype': x.dtype,
+*         'data': x.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': x.offset,
+*         'order': x.order
+*     },
+*     {
+*         'dtype': y.dtype,
+*         'data': y.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': y.offset,
+*         'order': y.order
+*     },
+*     {
+*         'dtype': z.dtype,
+*         'data': z.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': z.offset,
+*         'order': z.order
+*     }
+* ];
+*
+* // Define an input strategy:
+* function inputStrategy( x ) {
+*     return {
+*         'dtype': x.dtype,
+*         'data': x.data,
+*         'shape': [ 4 ],
+*         'strides': [ 1 ],
+*         'offset': x.offset,
+*         'order': x.order
+*     };
+* }
+*
+* // Define an output strategy:
+* function outputStrategy( x ) {
+*     return x;
+* }
+*
+* var strategy = {
+*     'input': inputStrategy,
+*     'output': outputStrategy
+* };
+*
+* // Apply strided function:
+* kernel( gwxpy, [ x, y, z ], views, [ 1, 1, 1, 1, 1, 3 ], [ 12, 12, 12, 12, 12, 4 ], [ 12, 12, 12, 12, 12, 4 ], [ 12, 12, 12, 12, 12, 4 ], strategy, strategy, strategy, {} );
+*
+* var arr = ndarray2array( z.data, z.shape, z.strides, z.offset, z.order );
+* // returns [ [ [ [ [ [ [ [ 3.0, 5.0 ], [ 7.0, 9.0 ] ], [ [ 11.0, 13.0 ], [ 15.0, 17.0 ] ], [ [ 19.0, 21.0 ], [ 23.0, 25.0 ] ] ] ] ] ] ] ]
+*/
+function kernel( fcn, arrays, views, shape, stridesX, stridesY, stridesZ, strategyX, strategyY, strategyZ, opts ) { // eslint-disable-line max-len, max-params
+	var dv0;
+	var dv1;
+	var dv2;
+	var dv3;
+	var dv4;
+	var dv5;
+	var S0;
+	var S1;
+	var S2;
+	var S3;
+	var S4;
+	var S5;
+	var sv;
+	var iv;
+	var i0;
+	var i1;
+	var i2;
+	var i3;
+	var i4;
+	var i5;
+	var v;
+	var i;
+
+	// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...
+
+	// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...
+	if ( isRowMajor( stridesX ) ) {
+		// For row-major ndarrays, the last dimensions have the fastest changing indices...
+		S0 = shape[ 5 ];
+		S1 = shape[ 4 ];
+		S2 = shape[ 3 ];
+		S3 = shape[ 2 ];
+		S4 = shape[ 1 ];
+		S5 = shape[ 0 ];
+		dv0 = [                                   // offset increment for innermost loop
+			stridesX[5],
+			stridesY[5],
+			stridesZ[5]
+		];
+		dv1 = [
+			stridesX[4] - ( S0*stridesX[5] ),
+			stridesY[4] - ( S0*stridesY[5] ),
+			stridesZ[4] - ( S0*stridesZ[5] )
+		];
+		dv2 = [
+			stridesX[3] - ( S1*stridesX[4] ),
+			stridesY[3] - ( S1*stridesY[4] ),
+			stridesZ[3] - ( S1*stridesZ[4] )
+		];
+		dv3 = [
+			stridesX[2] - ( S2*stridesX[3] ),
+			stridesY[2] - ( S2*stridesY[3] ),
+			stridesZ[2] - ( S2*stridesZ[3] )
+		];
+		dv4 = [
+			stridesX[1] - ( S3*stridesX[2] ),
+			stridesY[1] - ( S3*stridesY[2] ),
+			stridesZ[1] - ( S3*stridesZ[2] )
+		];
+		dv5 = [                                   // offset increment for outermost loop
+			stridesX[0] - ( S4*stridesX[1] ),
+			stridesY[0] - ( S4*stridesY[1] ),
+			stridesZ[0] - ( S4*stridesZ[1] )
+		];
+		for ( i = 3; i < arrays.length; i++ ) {
+			sv = arrays[ i ].strides;
+			dv0.push( sv[5] );
+			dv1.push( sv[4] - ( S0*sv[5] ) );
+			dv2.push( sv[3] - ( S1*sv[4] ) );
+			dv3.push( sv[2] - ( S2*sv[3] ) );
+			dv4.push( sv[1] - ( S3*sv[2] ) );
+			dv5.push( sv[0] - ( S4*sv[1] ) );
+		}
+	} else { // order === 'column-major'
+		// For column-major ndarrays, the first dimensions have the fastest changing indices...
+		S0 = shape[ 0 ];
+		S1 = shape[ 1 ];
+		S2 = shape[ 2 ];
+		S3 = shape[ 3 ];
+		S4 = shape[ 4 ];
+		S5 = shape[ 5 ];
+		dv0 = [                                   // offset increment for innermost loop
+			stridesX[0],
+			stridesY[0],
+			stridesZ[0]
+		];
+		dv1 = [
+			stridesX[1] - ( S0*stridesX[0] ),
+			stridesY[1] - ( S0*stridesY[0] ),
+			stridesZ[1] - ( S0*stridesZ[0] )
+		];
+		dv2 = [
+			stridesX[2] - ( S1*stridesX[1] ),
+			stridesY[2] - ( S1*stridesY[1] ),
+			stridesZ[2] - ( S1*stridesZ[1] )
+		];
+		dv3 = [
+			stridesX[3] - ( S2*stridesX[2] ),
+			stridesY[3] - ( S2*stridesY[2] ),
+			stridesZ[3] - ( S2*stridesZ[2] )
+		];
+		dv4 = [
+			stridesX[4] - ( S3*stridesX[3] ),
+			stridesY[4] - ( S3*stridesY[3] ),
+			stridesZ[4] - ( S3*stridesZ[3] )
+		];
+		dv5 = [                                   // offset increment for outermost loop
+			stridesX[5] - ( S4*stridesX[4] ),
+			stridesY[5] - ( S4*stridesY[4] ),
+			stridesZ[5] - ( S4*stridesZ[4] )
+		];
+		for ( i = 3; i < arrays.length; i++ ) {
+			sv = arrays[ i ].strides;
+			dv0.push( sv[0] );
+			dv1.push( sv[1] - ( S0*sv[0] ) );
+			dv2.push( sv[2] - ( S1*sv[1] ) );
+			dv3.push( sv[3] - ( S2*sv[2] ) );
+			dv4.push( sv[4] - ( S3*sv[3] ) );
+			dv5.push( sv[5] - ( S4*sv[4] ) );
+		}
+	}
+	// Resolve a list of pointers to the first indexed elements in the respective ndarrays:
+	iv = offsets( arrays );
+
+	// Shallow copy the list of views to an internal array so that we can update with reshaped views without impacting the original list of views:
+	v = copyIndexed( views );
+
+	// Iterate over the loop dimensions...
+	for ( i5 = 0; i5 < S5; i5++ ) {
+		for ( i4 = 0; i4 < S4; i4++ ) {
+			for ( i3 = 0; i3 < S3; i3++ ) {
+				for ( i2 = 0; i2 < S2; i2++ ) {
+					for ( i1 = 0; i1 < S1; i1++ ) {
+						for ( i0 = 0; i0 < S0; i0++ ) {
+							setViewOffsets( views, iv );
+							v[ 0 ] = strategyX.input( views[ 0 ] );
+							v[ 1 ] = strategyY.input( views[ 1 ] );
+							v[ 2 ] = strategyZ.input( views[ 2 ] );
+							fcn( v, opts );
+							strategyZ.output( views[ 2 ] );
+							incrementOffsets( iv, dv0 );
+						}
+						incrementOffsets( iv, dv1 );
+					}
+					incrementOffsets( iv, dv2 );
+				}
+				incrementOffsets( iv, dv3 );
+			}
+			incrementOffsets( iv, dv4 );
+		}
+		incrementOffsets( iv, dv5 );
+	}
+}
+
+
+// EXPORTS //
+
+module.exports = kernel;
diff --git a/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/7d.js b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/7d.js
new file mode 100644
index 000000000000..a0de93050407
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/7d.js
@@ -0,0 +1,339 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/* eslint-disable max-depth */
+
+'use strict';
+
+// MODULES //
+
+var isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major' );
+var copyIndexed = require( '@stdlib/array/base/copy-indexed' );
+var incrementOffsets = require( '@stdlib/ndarray/base/kernels/utils/increment-offsets' );
+var setViewOffsets = require( '@stdlib/ndarray/base/set-descriptor-offsets' );
+var offsets = require( '@stdlib/ndarray/base/offsets' );
+
+
+// MAIN //
+
+/**
+* Applies a one-dimensional strided array function to a list of specified dimensions in two input ndarrays and assigns results to a provided output ndarray.
+*
+* @private
+* @param {Function} fcn - wrapper for a one-dimensional strided array function
+* @param {Array<Object>} arrays - ndarray descriptors
+* @param {Array<Object>} views - initialized ndarray descriptors representing subarray views
+* @param {Array<integer>} shape - loop dimensions
+* @param {Array<integer>} stridesX - loop dimension strides for the first input ndarray
+* @param {Array<integer>} stridesY - loop dimension strides for the second input ndarray
+* @param {Array<integer>} stridesZ - loop dimension strides for the output ndarray
+* @param {Object} strategyX - strategy for marshaling data to and from a first input ndarray view
+* @param {Object} strategyY - strategy for marshaling data to and from a second input ndarray view
+* @param {Object} strategyZ - strategy for marshaling data to and from an output ndarray view
+* @param {Options} opts - function options
+* @returns {void}
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+* var gwxpy = require( '@stdlib/blas/ext/base/ndarray/gwxpy' );
+*
+* // Create data buffers:
+* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+* var ybuf = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 ] );
+* var zbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+*
+* // Define the array shapes:
+* var xsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];
+* var ysh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];
+* var zsh = [ 1, 1, 1, 1, 1, 1, 3, 2, 2 ];
+*
+* // Define the array strides:
+* var sx = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];
+* var sy = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];
+* var sz = [ 12, 12, 12, 12, 12, 12, 4, 2, 1 ];
+*
+* // Define the index offsets:
+* var ox = 0;
+* var oy = 0;
+* var oz = 0;
+*
+* // Create the input ndarray descriptors:
+* var x = {
+*     'dtype': 'float64',
+*     'data': xbuf,
+*     'shape': xsh,
+*     'strides': sx,
+*     'offset': ox,
+*     'order': 'row-major'
+* };
+*
+* var y = {
+*     'dtype': 'float64',
+*     'data': ybuf,
+*     'shape': ysh,
+*     'strides': sy,
+*     'offset': oy,
+*     'order': 'row-major'
+* };
+*
+* // Create an output ndarray descriptor:
+* var z = {
+*     'dtype': 'float64',
+*     'data': zbuf,
+*     'shape': zsh,
+*     'strides': sz,
+*     'offset': oz,
+*     'order': 'row-major'
+* };
+*
+* // Initialize ndarray descriptors representing subarray views:
+* var views = [
+*     {
+*         'dtype': x.dtype,
+*         'data': x.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': x.offset,
+*         'order': x.order
+*     },
+*     {
+*         'dtype': y.dtype,
+*         'data': y.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': y.offset,
+*         'order': y.order
+*     },
+*     {
+*         'dtype': z.dtype,
+*         'data': z.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': z.offset,
+*         'order': z.order
+*     }
+* ];
+*
+* // Define an input strategy:
+* function inputStrategy( x ) {
+*     return {
+*         'dtype': x.dtype,
+*         'data': x.data,
+*         'shape': [ 4 ],
+*         'strides': [ 1 ],
+*         'offset': x.offset,
+*         'order': x.order
+*     };
+* }
+*
+* // Define an output strategy:
+* function outputStrategy( x ) {
+*     return x;
+* }
+*
+* var strategy = {
+*     'input': inputStrategy,
+*     'output': outputStrategy
+* };
+*
+* // Apply strided function:
+* kernel( gwxpy, [ x, y, z ], views, [ 1, 1, 1, 1, 1, 1, 3 ], [ 12, 12, 12, 12, 12, 12, 4 ], [ 12, 12, 12, 12, 12, 12, 4 ], [ 12, 12, 12, 12, 12, 12, 4 ], strategy, strategy, strategy, {} );
+*
+* var arr = ndarray2array( z.data, z.shape, z.strides, z.offset, z.order );
+* // returns [ [ [ [ [ [ [ [ [ 3.0, 5.0 ], [ 7.0, 9.0 ] ], [ [ 11.0, 13.0 ], [ 15.0, 17.0 ] ], [ [ 19.0, 21.0 ], [ 23.0, 25.0 ] ] ] ] ] ] ] ] ]
+*/
+function kernel( fcn, arrays, views, shape, stridesX, stridesY, stridesZ, strategyX, strategyY, strategyZ, opts ) { // eslint-disable-line max-len, max-params
+	var dv0;
+	var dv1;
+	var dv2;
+	var dv3;
+	var dv4;
+	var dv5;
+	var dv6;
+	var S0;
+	var S1;
+	var S2;
+	var S3;
+	var S4;
+	var S5;
+	var S6;
+	var sv;
+	var iv;
+	var i0;
+	var i1;
+	var i2;
+	var i3;
+	var i4;
+	var i5;
+	var i6;
+	var v;
+	var i;
+
+	// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...
+
+	// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...
+	if ( isRowMajor( stridesX ) ) {
+		// For row-major ndarrays, the last dimensions have the fastest changing indices...
+		S0 = shape[ 6 ];
+		S1 = shape[ 5 ];
+		S2 = shape[ 4 ];
+		S3 = shape[ 3 ];
+		S4 = shape[ 2 ];
+		S5 = shape[ 1 ];
+		S6 = shape[ 0 ];
+		dv0 = [                                   // offset increment for innermost loop
+			stridesX[6],
+			stridesY[6],
+			stridesZ[6]
+		];
+		dv1 = [
+			stridesX[5] - ( S0*stridesX[6] ),
+			stridesY[5] - ( S0*stridesY[6] ),
+			stridesZ[5] - ( S0*stridesZ[6] )
+		];
+		dv2 = [
+			stridesX[4] - ( S1*stridesX[5] ),
+			stridesY[4] - ( S1*stridesY[5] ),
+			stridesZ[4] - ( S1*stridesZ[5] )
+		];
+		dv3 = [
+			stridesX[3] - ( S2*stridesX[4] ),
+			stridesY[3] - ( S2*stridesY[4] ),
+			stridesZ[3] - ( S2*stridesZ[4] )
+		];
+		dv4 = [
+			stridesX[2] - ( S3*stridesX[3] ),
+			stridesY[2] - ( S3*stridesY[3] ),
+			stridesZ[2] - ( S3*stridesZ[3] )
+		];
+		dv5 = [
+			stridesX[1] - ( S4*stridesX[2] ),
+			stridesY[1] - ( S4*stridesY[2] ),
+			stridesZ[1] - ( S4*stridesZ[2] )
+		];
+		dv6 = [                                   // offset increment for outermost loop
+			stridesX[0] - ( S5*stridesX[1] ),
+			stridesY[0] - ( S5*stridesY[1] ),
+			stridesZ[0] - ( S5*stridesZ[1] )
+		];
+		for ( i = 3; i < arrays.length; i++ ) {
+			sv = arrays[ i ].strides;
+			dv0.push( sv[6] );
+			dv1.push( sv[5] - ( S0*sv[6] ) );
+			dv2.push( sv[4] - ( S1*sv[5] ) );
+			dv3.push( sv[3] - ( S2*sv[4] ) );
+			dv4.push( sv[2] - ( S3*sv[3] ) );
+			dv5.push( sv[1] - ( S4*sv[2] ) );
+			dv6.push( sv[0] - ( S5*sv[1] ) );
+		}
+	} else { // order === 'column-major'
+		// For column-major ndarrays, the first dimensions have the fastest changing indices...
+		S0 = shape[ 0 ];
+		S1 = shape[ 1 ];
+		S2 = shape[ 2 ];
+		S3 = shape[ 3 ];
+		S4 = shape[ 4 ];
+		S5 = shape[ 5 ];
+		S6 = shape[ 6 ];
+		dv0 = [                                   // offset increment for innermost loop
+			stridesX[0],
+			stridesY[0],
+			stridesZ[0]
+		];
+		dv1 = [
+			stridesX[1] - ( S0*stridesX[0] ),
+			stridesY[1] - ( S0*stridesY[0] ),
+			stridesZ[1] - ( S0*stridesZ[0] )
+		];
+		dv2 = [
+			stridesX[2] - ( S1*stridesX[1] ),
+			stridesY[2] - ( S1*stridesY[1] ),
+			stridesZ[2] - ( S1*stridesZ[1] )
+		];
+		dv3 = [
+			stridesX[3] - ( S2*stridesX[2] ),
+			stridesY[3] - ( S2*stridesY[2] ),
+			stridesZ[3] - ( S2*stridesZ[2] )
+		];
+		dv4 = [
+			stridesX[4] - ( S3*stridesX[3] ),
+			stridesY[4] - ( S3*stridesY[3] ),
+			stridesZ[4] - ( S3*stridesZ[3] )
+		];
+		dv5 = [
+			stridesX[5] - ( S4*stridesX[4] ),
+			stridesY[5] - ( S4*stridesY[4] ),
+			stridesZ[5] - ( S4*stridesZ[4] )
+		];
+		dv6 = [                                   // offset increment for outermost loop
+			stridesX[6] - ( S5*stridesX[5] ),
+			stridesY[6] - ( S5*stridesY[5] ),
+			stridesZ[6] - ( S5*stridesZ[5] )
+		];
+		for ( i = 3; i < arrays.length; i++ ) {
+			sv = arrays[ i ].strides;
+			dv0.push( sv[0] );
+			dv1.push( sv[1] - ( S0*sv[0] ) );
+			dv2.push( sv[2] - ( S1*sv[1] ) );
+			dv3.push( sv[3] - ( S2*sv[2] ) );
+			dv4.push( sv[4] - ( S3*sv[3] ) );
+			dv5.push( sv[5] - ( S4*sv[4] ) );
+			dv6.push( sv[6] - ( S5*sv[5] ) );
+		}
+	}
+	// Resolve a list of pointers to the first indexed elements in the respective ndarrays:
+	iv = offsets( arrays );
+
+	// Shallow copy the list of views to an internal array so that we can update with reshaped views without impacting the original list of views:
+	v = copyIndexed( views );
+
+	// Iterate over the loop dimensions...
+	for ( i6 = 0; i6 < S6; i6++ ) {
+		for ( i5 = 0; i5 < S5; i5++ ) {
+			for ( i4 = 0; i4 < S4; i4++ ) {
+				for ( i3 = 0; i3 < S3; i3++ ) {
+					for ( i2 = 0; i2 < S2; i2++ ) {
+						for ( i1 = 0; i1 < S1; i1++ ) {
+							for ( i0 = 0; i0 < S0; i0++ ) {
+								setViewOffsets( views, iv );
+								v[ 0 ] = strategyX.input( views[ 0 ] );
+								v[ 1 ] = strategyY.input( views[ 1 ] );
+								v[ 2 ] = strategyZ.input( views[ 2 ] );
+								fcn( v, opts );
+								strategyZ.output( views[ 2 ] );
+								incrementOffsets( iv, dv0 );
+							}
+							incrementOffsets( iv, dv1 );
+						}
+						incrementOffsets( iv, dv2 );
+					}
+					incrementOffsets( iv, dv3 );
+				}
+				incrementOffsets( iv, dv4 );
+			}
+			incrementOffsets( iv, dv5 );
+		}
+		incrementOffsets( iv, dv6 );
+	}
+}
+
+
+// EXPORTS //
+
+module.exports = kernel;
diff --git a/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/8d.js b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/8d.js
new file mode 100644
index 000000000000..c82267272128
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/8d.js
@@ -0,0 +1,359 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/* eslint-disable max-depth */
+
+'use strict';
+
+// MODULES //
+
+var isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major' );
+var copyIndexed = require( '@stdlib/array/base/copy-indexed' );
+var incrementOffsets = require( '@stdlib/ndarray/base/kernels/utils/increment-offsets' );
+var setViewOffsets = require( '@stdlib/ndarray/base/set-descriptor-offsets' );
+var offsets = require( '@stdlib/ndarray/base/offsets' );
+
+
+// MAIN //
+
+/**
+* Applies a one-dimensional strided array function to a list of specified dimensions in two input ndarrays and assigns results to a provided output ndarray.
+*
+* @private
+* @param {Function} fcn - wrapper for a one-dimensional strided array function
+* @param {Array<Object>} arrays - ndarray descriptors
+* @param {Array<Object>} views - initialized ndarray descriptors representing subarray views
+* @param {Array<integer>} shape - loop dimensions
+* @param {Array<integer>} stridesX - loop dimension strides for the first input ndarray
+* @param {Array<integer>} stridesY - loop dimension strides for the second input ndarray
+* @param {Array<integer>} stridesZ - loop dimension strides for the output ndarray
+* @param {Object} strategyX - strategy for marshaling data to and from a first input ndarray view
+* @param {Object} strategyY - strategy for marshaling data to and from a second input ndarray view
+* @param {Object} strategyZ - strategy for marshaling data to and from an output ndarray view
+* @param {Options} opts - function options
+* @returns {void}
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+* var gwxpy = require( '@stdlib/blas/ext/base/ndarray/gwxpy' );
+*
+* // Create data buffers:
+* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+* var ybuf = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 ] );
+* var zbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+*
+* // Define the array shapes:
+* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];
+* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];
+* var zsh = [ 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];
+*
+* // Define the array strides:
+* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];
+* var sy = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];
+* var sz = [ 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];
+*
+* // Define the index offsets:
+* var ox = 0;
+* var oy = 0;
+* var oz = 0;
+*
+* // Create the input ndarray descriptors:
+* var x = {
+*     'dtype': 'float64',
+*     'data': xbuf,
+*     'shape': xsh,
+*     'strides': sx,
+*     'offset': ox,
+*     'order': 'row-major'
+* };
+*
+* var y = {
+*     'dtype': 'float64',
+*     'data': ybuf,
+*     'shape': ysh,
+*     'strides': sy,
+*     'offset': oy,
+*     'order': 'row-major'
+* };
+*
+* // Create an output ndarray descriptor:
+* var z = {
+*     'dtype': 'float64',
+*     'data': zbuf,
+*     'shape': zsh,
+*     'strides': sz,
+*     'offset': oz,
+*     'order': 'row-major'
+* };
+*
+* // Initialize ndarray descriptors representing subarray views:
+* var views = [
+*     {
+*         'dtype': x.dtype,
+*         'data': x.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': x.offset,
+*         'order': x.order
+*     },
+*     {
+*         'dtype': y.dtype,
+*         'data': y.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': y.offset,
+*         'order': y.order
+*     },
+*     {
+*         'dtype': z.dtype,
+*         'data': z.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': z.offset,
+*         'order': z.order
+*     }
+* ];
+*
+* // Define an input strategy:
+* function inputStrategy( x ) {
+*     return {
+*         'dtype': x.dtype,
+*         'data': x.data,
+*         'shape': [ 4 ],
+*         'strides': [ 1 ],
+*         'offset': x.offset,
+*         'order': x.order
+*     };
+* }
+*
+* // Define an output strategy:
+* function outputStrategy( x ) {
+*     return x;
+* }
+*
+* var strategy = {
+*     'input': inputStrategy,
+*     'output': outputStrategy
+* };
+*
+* // Apply strided function:
+* kernel( gwxpy, [ x, y, z ], views, [ 1, 1, 1, 1, 1, 1, 1, 3 ], [ 12, 12, 12, 12, 12, 12, 12, 4 ], [ 12, 12, 12, 12, 12, 12, 12, 4 ], [ 12, 12, 12, 12, 12, 12, 12, 4 ], strategy, strategy, strategy, {} );
+*
+* var arr = ndarray2array( z.data, z.shape, z.strides, z.offset, z.order );
+* // returns [ [ [ [ [ [ [ [ [ [ 3.0, 5.0 ], [ 7.0, 9.0 ] ], [ [ 11.0, 13.0 ], [ 15.0, 17.0 ] ], [ [ 19.0, 21.0 ], [ 23.0, 25.0 ] ] ] ] ] ] ] ] ] ]
+*/
+function kernel( fcn, arrays, views, shape, stridesX, stridesY, stridesZ, strategyX, strategyY, strategyZ, opts ) { // eslint-disable-line max-len, max-params, max-statements
+	var dv0;
+	var dv1;
+	var dv2;
+	var dv3;
+	var dv4;
+	var dv5;
+	var dv6;
+	var dv7;
+	var S0;
+	var S1;
+	var S2;
+	var S3;
+	var S4;
+	var S5;
+	var S6;
+	var S7;
+	var sv;
+	var iv;
+	var i0;
+	var i1;
+	var i2;
+	var i3;
+	var i4;
+	var i5;
+	var i6;
+	var i7;
+	var v;
+	var i;
+
+	// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...
+
+	// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...
+	if ( isRowMajor( stridesX ) ) {
+		// For row-major ndarrays, the last dimensions have the fastest changing indices...
+		S0 = shape[ 7 ];
+		S1 = shape[ 6 ];
+		S2 = shape[ 5 ];
+		S3 = shape[ 4 ];
+		S4 = shape[ 3 ];
+		S5 = shape[ 2 ];
+		S6 = shape[ 1 ];
+		S7 = shape[ 0 ];
+		dv0 = [                                   // offset increment for innermost loop
+			stridesX[7],
+			stridesY[7],
+			stridesZ[7]
+		];
+		dv1 = [
+			stridesX[6] - ( S0*stridesX[7] ),
+			stridesY[6] - ( S0*stridesY[7] ),
+			stridesZ[6] - ( S0*stridesZ[7] )
+		];
+		dv2 = [
+			stridesX[5] - ( S1*stridesX[6] ),
+			stridesY[5] - ( S1*stridesY[6] ),
+			stridesZ[5] - ( S1*stridesZ[6] )
+		];
+		dv3 = [
+			stridesX[4] - ( S2*stridesX[5] ),
+			stridesY[4] - ( S2*stridesY[5] ),
+			stridesZ[4] - ( S2*stridesZ[5] )
+		];
+		dv4 = [
+			stridesX[3] - ( S3*stridesX[4] ),
+			stridesY[3] - ( S3*stridesY[4] ),
+			stridesZ[3] - ( S3*stridesZ[4] )
+		];
+		dv5 = [
+			stridesX[2] - ( S4*stridesX[3] ),
+			stridesY[2] - ( S4*stridesY[3] ),
+			stridesZ[2] - ( S4*stridesZ[3] )
+		];
+		dv6 = [
+			stridesX[1] - ( S5*stridesX[2] ),
+			stridesY[1] - ( S5*stridesY[2] ),
+			stridesZ[1] - ( S5*stridesZ[2] )
+		];
+		dv7 = [                                   // offset increment for outermost loop
+			stridesX[0] - ( S6*stridesX[1] ),
+			stridesY[0] - ( S6*stridesY[1] ),
+			stridesZ[0] - ( S6*stridesZ[1] )
+		];
+		for ( i = 3; i < arrays.length; i++ ) {
+			sv = arrays[ i ].strides;
+			dv0.push( sv[7] );
+			dv1.push( sv[6] - ( S0*sv[7] ) );
+			dv2.push( sv[5] - ( S1*sv[6] ) );
+			dv3.push( sv[4] - ( S2*sv[5] ) );
+			dv4.push( sv[3] - ( S3*sv[4] ) );
+			dv5.push( sv[2] - ( S4*sv[3] ) );
+			dv6.push( sv[1] - ( S5*sv[2] ) );
+			dv7.push( sv[0] - ( S6*sv[1] ) );
+		}
+	} else { // order === 'column-major'
+		// For column-major ndarrays, the first dimensions have the fastest changing indices...
+		S0 = shape[ 0 ];
+		S1 = shape[ 1 ];
+		S2 = shape[ 2 ];
+		S3 = shape[ 3 ];
+		S4 = shape[ 4 ];
+		S5 = shape[ 5 ];
+		S6 = shape[ 6 ];
+		S7 = shape[ 7 ];
+		dv0 = [                                   // offset increment for innermost loop
+			stridesX[0],
+			stridesY[0],
+			stridesZ[0]
+		];
+		dv1 = [
+			stridesX[1] - ( S0*stridesX[0] ),
+			stridesY[1] - ( S0*stridesY[0] ),
+			stridesZ[1] - ( S0*stridesZ[0] )
+		];
+		dv2 = [
+			stridesX[2] - ( S1*stridesX[1] ),
+			stridesY[2] - ( S1*stridesY[1] ),
+			stridesZ[2] - ( S1*stridesZ[1] )
+		];
+		dv3 = [
+			stridesX[3] - ( S2*stridesX[2] ),
+			stridesY[3] - ( S2*stridesY[2] ),
+			stridesZ[3] - ( S2*stridesZ[2] )
+		];
+		dv4 = [
+			stridesX[4] - ( S3*stridesX[3] ),
+			stridesY[4] - ( S3*stridesY[3] ),
+			stridesZ[4] - ( S3*stridesZ[3] )
+		];
+		dv5 = [
+			stridesX[5] - ( S4*stridesX[4] ),
+			stridesY[5] - ( S4*stridesY[4] ),
+			stridesZ[5] - ( S4*stridesZ[4] )
+		];
+		dv6 = [
+			stridesX[6] - ( S5*stridesX[5] ),
+			stridesY[6] - ( S5*stridesY[5] ),
+			stridesZ[6] - ( S5*stridesZ[5] )
+		];
+		dv7 = [                                   // offset increment for outermost loop
+			stridesX[7] - ( S6*stridesX[6] ),
+			stridesY[7] - ( S6*stridesY[6] ),
+			stridesZ[7] - ( S6*stridesZ[6] )
+		];
+		for ( i = 3; i < arrays.length; i++ ) {
+			sv = arrays[ i ].strides;
+			dv0.push( sv[0] );
+			dv1.push( sv[1] - ( S0*sv[0] ) );
+			dv2.push( sv[2] - ( S1*sv[1] ) );
+			dv3.push( sv[3] - ( S2*sv[2] ) );
+			dv4.push( sv[4] - ( S3*sv[3] ) );
+			dv5.push( sv[5] - ( S4*sv[4] ) );
+			dv6.push( sv[6] - ( S5*sv[5] ) );
+			dv7.push( sv[7] - ( S6*sv[6] ) );
+		}
+	}
+	// Resolve a list of pointers to the first indexed elements in the respective ndarrays:
+	iv = offsets( arrays );
+
+	// Shallow copy the list of views to an internal array so that we can update with reshaped views without impacting the original list of views:
+	v = copyIndexed( views );
+
+	// Iterate over the loop dimensions...
+	for ( i7 = 0; i7 < S7; i7++ ) {
+		for ( i6 = 0; i6 < S6; i6++ ) {
+			for ( i5 = 0; i5 < S5; i5++ ) {
+				for ( i4 = 0; i4 < S4; i4++ ) {
+					for ( i3 = 0; i3 < S3; i3++ ) {
+						for ( i2 = 0; i2 < S2; i2++ ) {
+							for ( i1 = 0; i1 < S1; i1++ ) {
+								for ( i0 = 0; i0 < S0; i0++ ) {
+									setViewOffsets( views, iv );
+									v[ 0 ] = strategyX.input( views[ 0 ] );
+									v[ 1 ] = strategyY.input( views[ 1 ] );
+									v[ 2 ] = strategyZ.input( views[ 2 ] );
+									fcn( v, opts );
+									strategyZ.output( views[ 2 ] );
+									incrementOffsets( iv, dv0 );
+								}
+								incrementOffsets( iv, dv1 );
+							}
+							incrementOffsets( iv, dv2 );
+						}
+						incrementOffsets( iv, dv3 );
+					}
+					incrementOffsets( iv, dv4 );
+				}
+				incrementOffsets( iv, dv5 );
+			}
+			incrementOffsets( iv, dv6 );
+		}
+		incrementOffsets( iv, dv7 );
+	}
+}
+
+
+// EXPORTS //
+
+module.exports = kernel;
diff --git a/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/9d.js b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/9d.js
new file mode 100644
index 000000000000..8cd2c131619b
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/9d.js
@@ -0,0 +1,379 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/* eslint-disable max-depth, max-len */
+
+'use strict';
+
+// MODULES //
+
+var isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major' );
+var copyIndexed = require( '@stdlib/array/base/copy-indexed' );
+var incrementOffsets = require( '@stdlib/ndarray/base/kernels/utils/increment-offsets' );
+var setViewOffsets = require( '@stdlib/ndarray/base/set-descriptor-offsets' );
+var offsets = require( '@stdlib/ndarray/base/offsets' );
+
+
+// MAIN //
+
+/**
+* Applies a one-dimensional strided array function to a list of specified dimensions in two input ndarrays and assigns results to a provided output ndarray.
+*
+* @private
+* @param {Function} fcn - wrapper for a one-dimensional strided array function
+* @param {Array<Object>} arrays - ndarray descriptors
+* @param {Array<Object>} views - initialized ndarray descriptors representing subarray views
+* @param {Array<integer>} shape - loop dimensions
+* @param {Array<integer>} stridesX - loop dimension strides for the first input ndarray
+* @param {Array<integer>} stridesY - loop dimension strides for the second input ndarray
+* @param {Array<integer>} stridesZ - loop dimension strides for the output ndarray
+* @param {Object} strategyX - strategy for marshaling data to and from a first input ndarray view
+* @param {Object} strategyY - strategy for marshaling data to and from a second input ndarray view
+* @param {Object} strategyZ - strategy for marshaling data to and from an output ndarray view
+* @param {Options} opts - function options
+* @returns {void}
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+* var gwxpy = require( '@stdlib/blas/ext/base/ndarray/gwxpy' );
+*
+* // Create data buffers:
+* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+* var ybuf = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 ] );
+* var zbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+*
+* // Define the array shapes:
+* var xsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];
+* var ysh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];
+* var zsh = [ 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2 ];
+*
+* // Define the array strides:
+* var sx = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];
+* var sy = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];
+* var sz = [ 12, 12, 12, 12, 12, 12, 12, 12, 4, 2, 1 ];
+*
+* // Define the index offsets:
+* var ox = 0;
+* var oy = 0;
+* var oz = 0;
+*
+* // Create the input ndarray descriptors:
+* var x = {
+*     'dtype': 'float64',
+*     'data': xbuf,
+*     'shape': xsh,
+*     'strides': sx,
+*     'offset': ox,
+*     'order': 'row-major'
+* };
+*
+* var y = {
+*     'dtype': 'float64',
+*     'data': ybuf,
+*     'shape': ysh,
+*     'strides': sy,
+*     'offset': oy,
+*     'order': 'row-major'
+* };
+*
+* // Create an output ndarray descriptor:
+* var z = {
+*     'dtype': 'float64',
+*     'data': zbuf,
+*     'shape': zsh,
+*     'strides': sz,
+*     'offset': oz,
+*     'order': 'row-major'
+* };
+*
+* // Initialize ndarray descriptors representing subarray views:
+* var views = [
+*     {
+*         'dtype': x.dtype,
+*         'data': x.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': x.offset,
+*         'order': x.order
+*     },
+*     {
+*         'dtype': y.dtype,
+*         'data': y.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': y.offset,
+*         'order': y.order
+*     },
+*     {
+*         'dtype': z.dtype,
+*         'data': z.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': z.offset,
+*         'order': z.order
+*     }
+* ];
+*
+* // Define an input strategy:
+* function inputStrategy( x ) {
+*     return {
+*         'dtype': x.dtype,
+*         'data': x.data,
+*         'shape': [ 4 ],
+*         'strides': [ 1 ],
+*         'offset': x.offset,
+*         'order': x.order
+*     };
+* }
+*
+* // Define an output strategy:
+* function outputStrategy( x ) {
+*     return x;
+* }
+*
+* var strategy = {
+*     'input': inputStrategy,
+*     'output': outputStrategy
+* };
+*
+* // Apply strided function:
+* kernel( gwxpy, [ x, y, z ], views, [ 1, 1, 1, 1, 1, 1, 1, 1, 3 ], [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], [ 12, 12, 12, 12, 12, 12, 12, 12, 4 ], strategy, strategy, strategy, {} );
+*
+* var arr = ndarray2array( z.data, z.shape, z.strides, z.offset, z.order );
+* // returns [ [ [ [ [ [ [ [ [ [ [ 3.0, 5.0 ], [ 7.0, 9.0 ] ], [ [ 11.0, 13.0 ], [ 15.0, 17.0 ] ], [ [ 19.0, 21.0 ], [ 23.0, 25.0 ] ] ] ] ] ] ] ] ] ] ]
+*/
+function kernel( fcn, arrays, views, shape, stridesX, stridesY, stridesZ, strategyX, strategyY, strategyZ, opts ) { // eslint-disable-line max-params, max-statements
+	var dv0;
+	var dv1;
+	var dv2;
+	var dv3;
+	var dv4;
+	var dv5;
+	var dv6;
+	var dv7;
+	var dv8;
+	var S0;
+	var S1;
+	var S2;
+	var S3;
+	var S4;
+	var S5;
+	var S6;
+	var S7;
+	var S8;
+	var sv;
+	var iv;
+	var i0;
+	var i1;
+	var i2;
+	var i3;
+	var i4;
+	var i5;
+	var i6;
+	var i7;
+	var i8;
+	var v;
+	var i;
+
+	// Note on variable naming convention: S#, dv#, i# where # corresponds to the loop number, with `0` being the innermost loop...
+
+	// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...
+	if ( isRowMajor( stridesX ) ) {
+		// For row-major ndarrays, the last dimensions have the fastest changing indices...
+		S0 = shape[ 8 ];
+		S1 = shape[ 7 ];
+		S2 = shape[ 6 ];
+		S3 = shape[ 5 ];
+		S4 = shape[ 4 ];
+		S5 = shape[ 3 ];
+		S6 = shape[ 2 ];
+		S7 = shape[ 1 ];
+		S8 = shape[ 0 ];
+		dv0 = [                                   // offset increment for innermost loop
+			stridesX[8],
+			stridesY[8],
+			stridesZ[8]
+		];
+		dv1 = [
+			stridesX[7] - ( S0*stridesX[8] ),
+			stridesY[7] - ( S0*stridesY[8] ),
+			stridesZ[7] - ( S0*stridesZ[8] )
+		];
+		dv2 = [
+			stridesX[6] - ( S1*stridesX[7] ),
+			stridesY[6] - ( S1*stridesY[7] ),
+			stridesZ[6] - ( S1*stridesZ[7] )
+		];
+		dv3 = [
+			stridesX[5] - ( S2*stridesX[6] ),
+			stridesY[5] - ( S2*stridesY[6] ),
+			stridesZ[5] - ( S2*stridesZ[6] )
+		];
+		dv4 = [
+			stridesX[4] - ( S3*stridesX[5] ),
+			stridesY[4] - ( S3*stridesY[5] ),
+			stridesZ[4] - ( S3*stridesZ[5] )
+		];
+		dv5 = [
+			stridesX[3] - ( S4*stridesX[4] ),
+			stridesY[3] - ( S4*stridesY[4] ),
+			stridesZ[3] - ( S4*stridesZ[4] )
+		];
+		dv6 = [
+			stridesX[2] - ( S5*stridesX[3] ),
+			stridesY[2] - ( S5*stridesY[3] ),
+			stridesZ[2] - ( S5*stridesZ[3] )
+		];
+		dv7 = [
+			stridesX[1] - ( S6*stridesX[2] ),
+			stridesY[1] - ( S6*stridesY[2] ),
+			stridesZ[1] - ( S6*stridesZ[2] )
+		];
+		dv8 = [                                   // offset increment for outermost loop
+			stridesX[0] - ( S7*stridesX[1] ),
+			stridesY[0] - ( S7*stridesY[1] ),
+			stridesZ[0] - ( S7*stridesZ[1] )
+		];
+		for ( i = 3; i < arrays.length; i++ ) {
+			sv = arrays[ i ].strides;
+			dv0.push( sv[8] );
+			dv1.push( sv[7] - ( S0*sv[8] ) );
+			dv2.push( sv[6] - ( S1*sv[7] ) );
+			dv3.push( sv[5] - ( S2*sv[6] ) );
+			dv4.push( sv[4] - ( S3*sv[5] ) );
+			dv5.push( sv[3] - ( S4*sv[4] ) );
+			dv6.push( sv[2] - ( S5*sv[3] ) );
+			dv7.push( sv[1] - ( S6*sv[2] ) );
+			dv8.push( sv[0] - ( S7*sv[1] ) );
+		}
+	} else { // order === 'column-major'
+		// For column-major ndarrays, the first dimensions have the fastest changing indices...
+		S0 = shape[ 0 ];
+		S1 = shape[ 1 ];
+		S2 = shape[ 2 ];
+		S3 = shape[ 3 ];
+		S4 = shape[ 4 ];
+		S5 = shape[ 5 ];
+		S6 = shape[ 6 ];
+		S7 = shape[ 7 ];
+		S8 = shape[ 8 ];
+		dv0 = [                                   // offset increment for innermost loop
+			stridesX[0],
+			stridesY[0],
+			stridesZ[0]
+		];
+		dv1 = [
+			stridesX[1] - ( S0*stridesX[0] ),
+			stridesY[1] - ( S0*stridesY[0] ),
+			stridesZ[1] - ( S0*stridesZ[0] )
+		];
+		dv2 = [
+			stridesX[2] - ( S1*stridesX[1] ),
+			stridesY[2] - ( S1*stridesY[1] ),
+			stridesZ[2] - ( S1*stridesZ[1] )
+		];
+		dv3 = [
+			stridesX[3] - ( S2*stridesX[2] ),
+			stridesY[3] - ( S2*stridesY[2] ),
+			stridesZ[3] - ( S2*stridesZ[2] )
+		];
+		dv4 = [
+			stridesX[4] - ( S3*stridesX[3] ),
+			stridesY[4] - ( S3*stridesY[3] ),
+			stridesZ[4] - ( S3*stridesZ[3] )
+		];
+		dv5 = [
+			stridesX[5] - ( S4*stridesX[4] ),
+			stridesY[5] - ( S4*stridesY[4] ),
+			stridesZ[5] - ( S4*stridesZ[4] )
+		];
+		dv6 = [
+			stridesX[6] - ( S5*stridesX[5] ),
+			stridesY[6] - ( S5*stridesY[5] ),
+			stridesZ[6] - ( S5*stridesZ[5] )
+		];
+		dv7 = [
+			stridesX[7] - ( S6*stridesX[6] ),
+			stridesY[7] - ( S6*stridesY[6] ),
+			stridesZ[7] - ( S6*stridesZ[6] )
+		];
+		dv8 = [                                   // offset increment for outermost loop
+			stridesX[8] - ( S7*stridesX[7] ),
+			stridesY[8] - ( S7*stridesY[7] ),
+			stridesZ[8] - ( S7*stridesZ[7] )
+		];
+		for ( i = 3; i < arrays.length; i++ ) {
+			sv = arrays[ i ].strides;
+			dv0.push( sv[0] );
+			dv1.push( sv[1] - ( S0*sv[0] ) );
+			dv2.push( sv[2] - ( S1*sv[1] ) );
+			dv3.push( sv[3] - ( S2*sv[2] ) );
+			dv4.push( sv[4] - ( S3*sv[3] ) );
+			dv5.push( sv[5] - ( S4*sv[4] ) );
+			dv6.push( sv[6] - ( S5*sv[5] ) );
+			dv7.push( sv[7] - ( S6*sv[6] ) );
+			dv8.push( sv[8] - ( S7*sv[7] ) );
+		}
+	}
+	// Resolve a list of pointers to the first indexed elements in the respective ndarrays:
+	iv = offsets( arrays );
+
+	// Shallow copy the list of views to an internal array so that we can update with reshaped views without impacting the original list of views:
+	v = copyIndexed( views );
+
+	// Iterate over the loop dimensions...
+	for ( i8 = 0; i8 < S8; i8++ ) {
+		for ( i7 = 0; i7 < S7; i7++ ) {
+			for ( i6 = 0; i6 < S6; i6++ ) {
+				for ( i5 = 0; i5 < S5; i5++ ) {
+					for ( i4 = 0; i4 < S4; i4++ ) {
+						for ( i3 = 0; i3 < S3; i3++ ) {
+							for ( i2 = 0; i2 < S2; i2++ ) {
+								for ( i1 = 0; i1 < S1; i1++ ) {
+									for ( i0 = 0; i0 < S0; i0++ ) {
+										setViewOffsets( views, iv );
+										v[ 0 ] = strategyX.input( views[ 0 ] );
+										v[ 1 ] = strategyY.input( views[ 1 ] );
+										v[ 2 ] = strategyZ.input( views[ 2 ] );
+										fcn( v, opts );
+										strategyZ.output( views[ 2 ] );
+										incrementOffsets( iv, dv0 );
+									}
+									incrementOffsets( iv, dv1 );
+								}
+								incrementOffsets( iv, dv2 );
+							}
+							incrementOffsets( iv, dv3 );
+						}
+						incrementOffsets( iv, dv4 );
+					}
+					incrementOffsets( iv, dv5 );
+				}
+				incrementOffsets( iv, dv6 );
+			}
+			incrementOffsets( iv, dv7 );
+		}
+		incrementOffsets( iv, dv8 );
+	}
+}
+
+
+// EXPORTS //
+
+module.exports = kernel;
diff --git a/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/index.js b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/index.js
new file mode 100644
index 000000000000..e6b643e9847c
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/index.js
@@ -0,0 +1,175 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Return a kernel for applying a one-dimensional strided array function to two input ndarrays and assigning results to an output ndarray.
+*
+* @module @stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+* var gwxpy = require( '@stdlib/blas/ext/base/ndarray/gwxpy' );
+* var kernel = require( '@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked' );
+*
+* // Create data buffers:
+* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+* var ybuf = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 ] );
+* var zbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+*
+* // Define the array shapes:
+* var xsh = [ 1, 3, 2, 2 ];
+* var ysh = [ 1, 3, 2, 2 ];
+* var zsh = [ 1, 3, 2, 2 ];
+*
+* // Define the array strides:
+* var sx = [ 12, 4, 2, 1 ];
+* var sy = [ 12, 4, 2, 1 ];
+* var sz = [ 12, 4, 2, 1 ];
+*
+* // Define the index offsets:
+* var ox = 0;
+* var oy = 0;
+* var oz = 0;
+*
+* // Create the input ndarray descriptors:
+* var x = {
+*     'dtype': 'float64',
+*     'data': xbuf,
+*     'shape': xsh,
+*     'strides': sx,
+*     'offset': ox,
+*     'order': 'row-major'
+* };
+*
+* var y = {
+*     'dtype': 'float64',
+*     'data': ybuf,
+*     'shape': ysh,
+*     'strides': sy,
+*     'offset': oy,
+*     'order': 'row-major'
+* };
+*
+* // Create an output ndarray descriptor:
+* var z = {
+*     'dtype': 'float64',
+*     'data': zbuf,
+*     'shape': zsh,
+*     'strides': sz,
+*     'offset': oz,
+*     'order': 'row-major'
+* };
+*
+* // Initialize ndarray descriptors representing subarray views:
+* var views = [
+*     {
+*         'dtype': x.dtype,
+*         'data': x.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': x.offset,
+*         'order': x.order
+*     },
+*     {
+*         'dtype': y.dtype,
+*         'data': y.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': y.offset,
+*         'order': y.order
+*     },
+*     {
+*         'dtype': z.dtype,
+*         'data': z.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': z.offset,
+*         'order': z.order
+*     }
+* ];
+*
+* // Define an input strategy:
+* function inputStrategy( x ) {
+*     return {
+*         'dtype': x.dtype,
+*         'data': x.data,
+*         'shape': [ 4 ],
+*         'strides': [ 1 ],
+*         'offset': x.offset,
+*         'order': x.order
+*     };
+* }
+*
+* // Define an output strategy:
+* function outputStrategy( x ) {
+*     return x;
+* }
+*
+* var strategy = {
+*     'input': inputStrategy,
+*     'output': outputStrategy
+* };
+*
+* // Resolve a kernel:
+* var f = kernel( 2 );
+*
+* // Apply strided function:
+* f( gwxpy, [ x, y, z ], views, [ 1, 3 ], [ 12, 4 ], [ 12, 4 ], [ 12, 4 ], strategy, strategy, strategy, {} );
+*
+* var arr = ndarray2array( z.data, z.shape, z.strides, z.offset, z.order );
+* // returns [ [ [ [ 3.0, 5.0 ], [ 7.0, 9.0 ] ], [ [ 11.0, 13.0 ], [ 15.0, 17.0 ] ], [ [ 19.0, 21.0 ], [ 23.0, 25.0 ] ] ] ]
+*/
+
+// MODULES //
+
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
+var kernel0d = require( './0d.js' );
+var kernel1d = require( './1d.js' );
+var kernel2d = require( './2d.js' );
+var kernel3d = require( './3d.js' );
+var kernel4d = require( './4d.js' );
+var kernel5d = require( './5d.js' );
+var kernel6d = require( './6d.js' );
+var kernel7d = require( './7d.js' );
+var kernel8d = require( './8d.js' );
+var kernel9d = require( './9d.js' );
+var kernel10d = require( './10d.js' );
+var main = require( './main.js' );
+
+
+// MAIN //
+
+setReadOnly( main, 'kernel0d', kernel0d );
+setReadOnly( main, 'kernel1d', kernel1d );
+setReadOnly( main, 'kernel2d', kernel2d );
+setReadOnly( main, 'kernel3d', kernel3d );
+setReadOnly( main, 'kernel4d', kernel4d );
+setReadOnly( main, 'kernel5d', kernel5d );
+setReadOnly( main, 'kernel6d', kernel6d );
+setReadOnly( main, 'kernel7d', kernel7d );
+setReadOnly( main, 'kernel8d', kernel8d );
+setReadOnly( main, 'kernel9d', kernel9d );
+setReadOnly( main, 'kernel10d', kernel10d );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/main.js b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/main.js
new file mode 100644
index 000000000000..879692c18a68
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/lib/main.js
@@ -0,0 +1,185 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var kernel0d = require( './0d.js' );
+var kernel1d = require( './1d.js' );
+var kernel2d = require( './2d.js' );
+var kernel3d = require( './3d.js' );
+var kernel4d = require( './4d.js' );
+var kernel5d = require( './5d.js' );
+var kernel6d = require( './6d.js' );
+var kernel7d = require( './7d.js' );
+var kernel8d = require( './8d.js' );
+var kernel9d = require( './9d.js' );
+var kernel10d = require( './10d.js' );
+
+
+// VARIABLES //
+
+var KERNELS = [
+	kernel0d,
+	kernel1d,
+	kernel2d,
+	kernel3d,
+	kernel4d,
+	kernel5d,
+	kernel6d,
+	kernel7d,
+	kernel8d,
+	kernel9d,
+	kernel10d
+];
+var MAX_DIMS = KERNELS.length - 1;
+
+
+// MAIN //
+
+/**
+* Returns a kernel for applying a one-dimensional strided array function to two input ndarrays and assigning results to an output ndarray.
+*
+* @param {integer} ndims - number of loop dimensions
+* @returns {(Function|null)} kernel function or null
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+* var gwxpy = require( '@stdlib/blas/ext/base/ndarray/gwxpy' );
+*
+* // Create data buffers:
+* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+* var ybuf = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 ] );
+* var zbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+*
+* // Define the array shapes:
+* var xsh = [ 1, 3, 2, 2 ];
+* var ysh = [ 1, 3, 2, 2 ];
+* var zsh = [ 1, 3, 2, 2 ];
+*
+* // Define the array strides:
+* var sx = [ 12, 4, 2, 1 ];
+* var sy = [ 12, 4, 2, 1 ];
+* var sz = [ 12, 4, 2, 1 ];
+*
+* // Define the index offsets:
+* var ox = 0;
+* var oy = 0;
+* var oz = 0;
+*
+* // Create the input ndarray descriptors:
+* var x = {
+*     'dtype': 'float64',
+*     'data': xbuf,
+*     'shape': xsh,
+*     'strides': sx,
+*     'offset': ox,
+*     'order': 'row-major'
+* };
+*
+* var y = {
+*     'dtype': 'float64',
+*     'data': ybuf,
+*     'shape': ysh,
+*     'strides': sy,
+*     'offset': oy,
+*     'order': 'row-major'
+* };
+*
+* // Create an output ndarray descriptor:
+* var z = {
+*     'dtype': 'float64',
+*     'data': zbuf,
+*     'shape': zsh,
+*     'strides': sz,
+*     'offset': oz,
+*     'order': 'row-major'
+* };
+*
+* // Initialize ndarray descriptors representing subarray views:
+* var views = [
+*     {
+*         'dtype': x.dtype,
+*         'data': x.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': x.offset,
+*         'order': x.order
+*     },
+*     {
+*         'dtype': y.dtype,
+*         'data': y.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': y.offset,
+*         'order': y.order
+*     },
+*     {
+*         'dtype': z.dtype,
+*         'data': z.data,
+*         'shape': [ 2, 2 ],
+*         'strides': [ 2, 1 ],
+*         'offset': z.offset,
+*         'order': z.order
+*     }
+* ];
+*
+* // Define an input strategy:
+* function inputStrategy( x ) {
+*     return {
+*         'dtype': x.dtype,
+*         'data': x.data,
+*         'shape': [ 4 ],
+*         'strides': [ 1 ],
+*         'offset': x.offset,
+*         'order': x.order
+*     };
+* }
+*
+* // Define an output strategy:
+* function outputStrategy( x ) {
+*     return x;
+* }
+*
+* var strategy = {
+*     'input': inputStrategy,
+*     'output': outputStrategy
+* };
+*
+* // Resolve a kernel:
+* var f = kernel( 2 );
+*
+* // Apply strided function:
+* f( gwxpy, [ x, y, z ], views, [ 1, 3 ], [ 12, 4 ], [ 12, 4 ], [ 12, 4 ], strategy, strategy, strategy, {} );
+*
+* var arr = ndarray2array( z.data, z.shape, z.strides, z.offset, z.order );
+* // returns [ [ [ [ 3.0, 5.0 ], [ 7.0, 9.0 ] ], [ [ 11.0, 13.0 ], [ 15.0, 17.0 ] ], [ [ 19.0, 21.0 ], [ 23.0, 25.0 ] ] ] ]
+*/
+function kernel( ndims ) {
+	if ( ndims < 0 || ndims > MAX_DIMS ) {
+		return null;
+	}
+	return KERNELS[ ndims ];
+}
+
+
+// EXPORTS //
+
+module.exports = kernel;
diff --git a/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/package.json b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/package.json
new file mode 100644
index 000000000000..b3dfe425c197
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/package.json
@@ -0,0 +1,65 @@
+{
+  "name": "@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked",
+  "version": "0.0.0",
+  "description": "Return a kernel for applying a one-dimensional strided array function to two input ndarrays and assigning results to an output ndarray.",
+  "license": "Apache-2.0",
+  "author": {
+    "name": "The Stdlib Authors",
+    "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+  },
+  "contributors": [
+    {
+      "name": "The Stdlib Authors",
+      "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+    }
+  ],
+  "main": "./lib",
+  "directories": {
+    "doc": "./docs",
+    "example": "./examples",
+    "lib": "./lib",
+    "test": "./test"
+  },
+  "types": "./docs/types",
+  "scripts": {},
+  "homepage": "https://github.com/stdlib-js/stdlib",
+  "repository": {
+    "type": "git",
+    "url": "git://github.com/stdlib-js/stdlib.git"
+  },
+  "bugs": {
+    "url": "https://github.com/stdlib-js/stdlib/issues"
+  },
+  "dependencies": {},
+  "devDependencies": {},
+  "engines": {
+    "node": ">=0.10.0",
+    "npm": ">2.7.0"
+  },
+  "os": [
+    "aix",
+    "darwin",
+    "freebsd",
+    "linux",
+    "macos",
+    "openbsd",
+    "sunos",
+    "win32",
+    "windows"
+  ],
+  "keywords": [
+    "stdlib",
+    "base",
+    "strided",
+    "array",
+    "ndarray",
+    "binary",
+    "apply",
+    "cumulative",
+    "accumulate",
+    "accumulation",
+    "vector",
+    "kernel"
+  ],
+  "__stdlib__": {}
+}
diff --git a/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/test/test.js b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/test/test.js
new file mode 100644
index 000000000000..053851cfb7f7
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/test/test.js
@@ -0,0 +1,35 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var kernel = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof kernel, 'function', 'main export is a function' );
+	t.end();
+});
+
+// FIXME: add tests

From 754e3bc3b4e317f5b17e9e7b235b9b9d7e1ef0c5 Mon Sep 17 00:00:00 2001
From: Athan <kgryte@gmail.com>
Date: Sat, 29 Aug 2026 17:12:56 -0700
Subject: [PATCH 2/4] style: fix missing linebreak

Signed-off-by: Athan <kgryte@gmail.com>
---
 .../kernels/generic/binary-strided1d/unblocked/docs/repl.txt     | 1 +
 1 file changed, 1 insertion(+)

diff --git a/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/docs/repl.txt b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/docs/repl.txt
index ef8d785a8002..045283ba0e80 100644
--- a/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/docs/repl.txt
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/docs/repl.txt
@@ -1,3 +1,4 @@
+
 {{alias}}( ndims )
     Returns a kernel for applying a one-dimensional strided array function to
     two input ndarrays and assigning results to an output ndarray.

From b3d5c6aa0e602275e61bd2d023d22bd488d4112a Mon Sep 17 00:00:00 2001
From: Athan <kgryte@gmail.com>
Date: Sat, 29 Aug 2026 17:15:30 -0700
Subject: [PATCH 3/4] docs: rename parameters

Signed-off-by: Athan <kgryte@gmail.com>
---
 .../binary-strided1d/unblocked/docs/repl.txt  | 88 +++++++++----------
 1 file changed, 44 insertions(+), 44 deletions(-)

diff --git a/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/docs/repl.txt b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/docs/repl.txt
index 045283ba0e80..e443b914307b 100644
--- a/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/docs/repl.txt
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/docs/repl.txt
@@ -41,7 +41,7 @@
     <Function>
 
 
-{{alias}}.kernel0d( fcn, arr, views, sh, sx, sy, sz, stX, stY, stZ, opts )
+{{alias}}.kernel0d( fcn, arr, views, sh, sx, sy, sz, stx, sty, stz, opts )
     Applies a one-dimensional strided array function to a list of specified
     dimensions in two input ndarrays and assigns results to a provided output
     ndarray.
@@ -74,20 +74,20 @@
     sz: Array<integer>
         Loop dimension strides for the output ndarray.
 
-    stX: Object
+    stx: Object
         Strategy for marshaling data to and from a first input ndarray view.
 
-    stY: Object
+    sty: Object
         Strategy for marshaling data to and from a second input ndarray view.
 
-    stZ: Object
+    stz: Object
         Strategy for marshaling data to and from an output ndarray view.
 
     opts: Object
         Function options which are passed through to `fcn`.
 
 
-{{alias}}.kernel1d( fcn, arr, views, sh, sx, sy, sz, stX, stY, stZ, opts )
+{{alias}}.kernel1d( fcn, arr, views, sh, sx, sy, sz, stx, sty, stz, opts )
     Applies a one-dimensional strided array function to a list of specified
     dimensions in two input ndarrays and assigns results to a provided output
     ndarray.
@@ -116,20 +116,20 @@
     sz: Array<integer>
         Loop dimension strides for the output ndarray.
 
-    stX: Object
+    stx: Object
         Strategy for marshaling data to and from a first input ndarray view.
 
-    stY: Object
+    sty: Object
         Strategy for marshaling data to and from a second input ndarray view.
 
-    stZ: Object
+    stz: Object
         Strategy for marshaling data to and from an output ndarray view.
 
     opts: Object
         Function options which are passed through to `fcn`.
 
 
-{{alias}}.kernel2d( fcn, arr, views, sh, sx, sy, sz, stX, stY, stZ, opts )
+{{alias}}.kernel2d( fcn, arr, views, sh, sx, sy, sz, stx, sty, stz, opts )
     Applies a one-dimensional strided array function to a list of specified
     dimensions in two input ndarrays and assigns results to a provided output
     ndarray.
@@ -158,20 +158,20 @@
     sz: Array<integer>
         Loop dimension strides for the output ndarray.
 
-    stX: Object
+    stx: Object
         Strategy for marshaling data to and from a first input ndarray view.
 
-    stY: Object
+    sty: Object
         Strategy for marshaling data to and from a second input ndarray view.
 
-    stZ: Object
+    stz: Object
         Strategy for marshaling data to and from an output ndarray view.
 
     opts: Object
         Function options which are passed through to `fcn`.
 
 
-{{alias}}.kernel3d( fcn, arr, views, sh, sx, sy, sz, stX, stY, stZ, opts )
+{{alias}}.kernel3d( fcn, arr, views, sh, sx, sy, sz, stx, sty, stz, opts )
     Applies a one-dimensional strided array function to a list of specified
     dimensions in two input ndarrays and assigns results to a provided output
     ndarray.
@@ -200,20 +200,20 @@
     sz: Array<integer>
         Loop dimension strides for the output ndarray.
 
-    stX: Object
+    stx: Object
         Strategy for marshaling data to and from a first input ndarray view.
 
-    stY: Object
+    sty: Object
         Strategy for marshaling data to and from a second input ndarray view.
 
-    stZ: Object
+    stz: Object
         Strategy for marshaling data to and from an output ndarray view.
 
     opts: Object
         Function options which are passed through to `fcn`.
 
 
-{{alias}}.kernel4d( fcn, arr, views, sh, sx, sy, sz, stX, stY, stZ, opts )
+{{alias}}.kernel4d( fcn, arr, views, sh, sx, sy, sz, stx, sty, stz, opts )
     Applies a one-dimensional strided array function to a list of specified
     dimensions in two input ndarrays and assigns results to a provided output
     ndarray.
@@ -242,20 +242,20 @@
     sz: Array<integer>
         Loop dimension strides for the output ndarray.
 
-    stX: Object
+    stx: Object
         Strategy for marshaling data to and from a first input ndarray view.
 
-    stY: Object
+    sty: Object
         Strategy for marshaling data to and from a second input ndarray view.
 
-    stZ: Object
+    stz: Object
         Strategy for marshaling data to and from an output ndarray view.
 
     opts: Object
         Function options which are passed through to `fcn`.
 
 
-{{alias}}.kernel5d( fcn, arr, views, sh, sx, sy, sz, stX, stY, stZ, opts )
+{{alias}}.kernel5d( fcn, arr, views, sh, sx, sy, sz, stx, sty, stz, opts )
     Applies a one-dimensional strided array function to a list of specified
     dimensions in two input ndarrays and assigns results to a provided output
     ndarray.
@@ -284,20 +284,20 @@
     sz: Array<integer>
         Loop dimension strides for the output ndarray.
 
-    stX: Object
+    stx: Object
         Strategy for marshaling data to and from a first input ndarray view.
 
-    stY: Object
+    sty: Object
         Strategy for marshaling data to and from a second input ndarray view.
 
-    stZ: Object
+    stz: Object
         Strategy for marshaling data to and from an output ndarray view.
 
     opts: Object
         Function options which are passed through to `fcn`.
 
 
-{{alias}}.kernel6d( fcn, arr, views, sh, sx, sy, sz, stX, stY, stZ, opts )
+{{alias}}.kernel6d( fcn, arr, views, sh, sx, sy, sz, stx, sty, stz, opts )
     Applies a one-dimensional strided array function to a list of specified
     dimensions in two input ndarrays and assigns results to a provided output
     ndarray.
@@ -326,20 +326,20 @@
     sz: Array<integer>
         Loop dimension strides for the output ndarray.
 
-    stX: Object
+    stx: Object
         Strategy for marshaling data to and from a first input ndarray view.
 
-    stY: Object
+    sty: Object
         Strategy for marshaling data to and from a second input ndarray view.
 
-    stZ: Object
+    stz: Object
         Strategy for marshaling data to and from an output ndarray view.
 
     opts: Object
         Function options which are passed through to `fcn`.
 
 
-{{alias}}.kernel7d( fcn, arr, views, sh, sx, sy, sz, stX, stY, stZ, opts )
+{{alias}}.kernel7d( fcn, arr, views, sh, sx, sy, sz, stx, sty, stz, opts )
     Applies a one-dimensional strided array function to a list of specified
     dimensions in two input ndarrays and assigns results to a provided output
     ndarray.
@@ -368,20 +368,20 @@
     sz: Array<integer>
         Loop dimension strides for the output ndarray.
 
-    stX: Object
+    stx: Object
         Strategy for marshaling data to and from a first input ndarray view.
 
-    stY: Object
+    sty: Object
         Strategy for marshaling data to and from a second input ndarray view.
 
-    stZ: Object
+    stz: Object
         Strategy for marshaling data to and from an output ndarray view.
 
     opts: Object
         Function options which are passed through to `fcn`.
 
 
-{{alias}}.kernel8d( fcn, arr, views, sh, sx, sy, sz, stX, stY, stZ, opts )
+{{alias}}.kernel8d( fcn, arr, views, sh, sx, sy, sz, stx, sty, stz, opts )
     Applies a one-dimensional strided array function to a list of specified
     dimensions in two input ndarrays and assigns results to a provided output
     ndarray.
@@ -410,20 +410,20 @@
     sz: Array<integer>
         Loop dimension strides for the output ndarray.
 
-    stX: Object
+    stx: Object
         Strategy for marshaling data to and from a first input ndarray view.
 
-    stY: Object
+    sty: Object
         Strategy for marshaling data to and from a second input ndarray view.
 
-    stZ: Object
+    stz: Object
         Strategy for marshaling data to and from an output ndarray view.
 
     opts: Object
         Function options which are passed through to `fcn`.
 
 
-{{alias}}.kernel9d( fcn, arr, views, sh, sx, sy, sz, stX, stY, stZ, opts )
+{{alias}}.kernel9d( fcn, arr, views, sh, sx, sy, sz, stx, sty, stz, opts )
     Applies a one-dimensional strided array function to a list of specified
     dimensions in two input ndarrays and assigns results to a provided output
     ndarray.
@@ -452,20 +452,20 @@
     sz: Array<integer>
         Loop dimension strides for the output ndarray.
 
-    stX: Object
+    stx: Object
         Strategy for marshaling data to and from a first input ndarray view.
 
-    stY: Object
+    sty: Object
         Strategy for marshaling data to and from a second input ndarray view.
 
-    stZ: Object
+    stz: Object
         Strategy for marshaling data to and from an output ndarray view.
 
     opts: Object
         Function options which are passed through to `fcn`.
 
 
-{{alias}}.kernel10d( fcn, arr, views, sh, sx, sy, sz, stX, stY, stZ, opts )
+{{alias}}.kernel10d( fcn, arr, views, sh, sx, sy, sz, stx, sty, stz, opts )
     Applies a one-dimensional strided array function to a list of specified
     dimensions in two input ndarrays and assigns results to a provided output
     ndarray.
@@ -494,13 +494,13 @@
     sz: Array<integer>
         Loop dimension strides for the output ndarray.
 
-    stX: Object
+    stx: Object
         Strategy for marshaling data to and from a first input ndarray view.
 
-    stY: Object
+    sty: Object
         Strategy for marshaling data to and from a second input ndarray view.
 
-    stZ: Object
+    stz: Object
         Strategy for marshaling data to and from an output ndarray view.
 
     opts: Object

From ce651154037237e180d2f76bde163ce5ffbba02c Mon Sep 17 00:00:00 2001
From: Athan <kgryte@gmail.com>
Date: Sat, 29 Aug 2026 17:29:56 -0700
Subject: [PATCH 4/4] docs: fix signatures

Signed-off-by: Athan <kgryte@gmail.com>
---
 .../binary-strided1d/unblocked/README.md      | 22 +++++++++----------
 1 file changed, 11 insertions(+), 11 deletions(-)

diff --git a/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/README.md b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/README.md
index 02a8d233eaca..3294ab75e920 100644
--- a/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/README.md
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/unblocked/README.md
@@ -185,7 +185,7 @@ The returned function iterates over ndarray elements according to the memory lay
 
 <!-- lint disable maximum-heading-length -->
 
-#### kernel.kernel.kernel0d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
+#### kernel.kernel0d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
 
 <!-- lint enable maximum-heading-length -->
 
@@ -294,7 +294,7 @@ The `views`, `shape`, `stridesX`, `stridesY`, and `stridesZ` parameters are unus
 
 <!-- lint disable maximum-heading-length -->
 
-#### kernel.kernel.kernel1d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
+#### kernel.kernel1d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
 
 <!-- lint enable maximum-heading-length -->
 
@@ -429,7 +429,7 @@ The function has the following parameters:
 
 <!-- lint disable maximum-heading-length -->
 
-#### kernel.kernel.kernel2d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
+#### kernel.kernel2d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
 
 <!-- lint enable maximum-heading-length -->
 
@@ -564,7 +564,7 @@ The function has the following parameters:
 
 <!-- lint disable maximum-heading-length -->
 
-#### kernel.kernel.kernel3d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
+#### kernel.kernel3d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
 
 <!-- lint enable maximum-heading-length -->
 
@@ -699,7 +699,7 @@ The function has the following parameters:
 
 <!-- lint disable maximum-heading-length -->
 
-#### kernel.kernel.kernel4d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
+#### kernel.kernel4d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
 
 <!-- lint enable maximum-heading-length -->
 
@@ -834,7 +834,7 @@ The function has the following parameters:
 
 <!-- lint disable maximum-heading-length -->
 
-#### kernel.kernel.kernel5d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
+#### kernel.kernel5d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
 
 <!-- lint enable maximum-heading-length -->
 
@@ -969,7 +969,7 @@ The function has the following parameters:
 
 <!-- lint disable maximum-heading-length -->
 
-#### kernel.kernel.kernel6d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
+#### kernel.kernel6d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
 
 <!-- lint enable maximum-heading-length -->
 
@@ -1104,7 +1104,7 @@ The function has the following parameters:
 
 <!-- lint disable maximum-heading-length -->
 
-#### kernel.kernel.kernel7d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
+#### kernel.kernel7d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
 
 <!-- lint enable maximum-heading-length -->
 
@@ -1239,7 +1239,7 @@ The function has the following parameters:
 
 <!-- lint disable maximum-heading-length -->
 
-#### kernel.kernel.kernel8d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
+#### kernel.kernel8d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
 
 <!-- lint enable maximum-heading-length -->
 
@@ -1374,7 +1374,7 @@ The function has the following parameters:
 
 <!-- lint disable maximum-heading-length -->
 
-#### kernel.kernel.kernel9d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
+#### kernel.kernel9d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
 
 <!-- lint enable maximum-heading-length -->
 
@@ -1509,7 +1509,7 @@ The function has the following parameters:
 
 <!-- lint disable maximum-heading-length -->
 
-#### kernel.kernel.kernel10d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
+#### kernel.kernel10d( fcn, arrays, views, shape, stridesX, strideY, strideZ, strategyX, strategyY, strategyZ, options )
 
 <!-- lint enable maximum-heading-length -->