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+<!--
+
+@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 using loop blocking.
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var kernel = require( '@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked' );
+```
+
+#### kernel( ndims )
+
+Returns a kernel for applying a one-dimensional strided array function to two input ndarrays and assigning results to an output ndarray using loop blocking.
+
+<!-- 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 `ndims < 2` or a value greater than the maximum number of supported loop dimensions, the function returns `null`.
+
+```javascript
+var f = kernel( 1 );
+// 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.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 using loop blocking.
+
+<!-- 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.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 using loop blocking.
+
+<!-- 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.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 using loop blocking.
+
+<!-- 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.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 using loop blocking.
+
+<!-- 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.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 using loop blocking.
+
+<!-- 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.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 using loop blocking.
+
+<!-- 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.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 using loop blocking.
+
+<!-- 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.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 using loop blocking.
+
+<!-- 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.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 using loop blocking.
+
+<!-- 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_).
+
+-   For very high-dimensional ndarrays which are non-contiguous, one should consider copying the underlying data to contiguous memory before performing an operation in order to achieve better performance.
+
+</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/blocked' );
+
+// 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/blocked/docs/repl.txt b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/docs/repl.txt
new file mode 100644
index 000000000000..e14e55d08a8d
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/docs/repl.txt
@@ -0,0 +1,424 @@
+
+{{alias}}( ndims )
+    Returns a kernel for applying a one-dimensional strided array function to
+    two input ndarrays and assigning results to an output ndarray using loop
+    blocking.
+
+    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 < 2` or 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}}.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 via loop blocking.
+
+    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 via loop blocking.
+
+    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 via loop blocking.
+
+    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 via loop blocking.
+
+    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 via loop blocking.
+
+    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 via loop blocking.
+
+    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 via loop blocking.
+
+    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 via loop blocking.
+
+    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 via loop blocking.
+
+    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/blocked/examples/index.js b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/examples/index.js
new file mode 100644
index 000000000000..62a43de2234c
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/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/blocked/lib/10d.js b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/lib/10d.js
new file mode 100644
index 000000000000..b35ba4fa0c5b
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/lib/10d.js
@@ -0,0 +1,433 @@
+/**
+* @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 loopOrder = require( '@stdlib/ndarray/base/binary-loop-interchange-order' );
+var blockSize = require( '@stdlib/ndarray/base/binary-tiling-block-size' );
+var takeIndexed = require( '@stdlib/array/base/take-indexed' );
+var copyIndexed = require( '@stdlib/array/base/copy-indexed' );
+var zeros = require( '@stdlib/array/base/zeros' );
+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 via loop blocking.
+*
+* @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' );
+* var strategy = require( '@stdlib/ndarray/base/kernels/generic/unary-strided1d/strategy' );
+*
+* // 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 input/output strategies for iterating over subarray views:
+* var strategyX = strategy( views[ 0 ] );
+* var strategyY = strategy( views[ 1 ] );
+* var strategyZ = strategy( views[ 2 ] );
+*
+* // 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 ], strategyX, strategyY, strategyZ, {} );
+*
+* 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 bsize;
+	var dv0;
+	var dv1;
+	var dv2;
+	var dv3;
+	var dv4;
+	var dv5;
+	var dv6;
+	var dv7;
+	var dv8;
+	var dv9;
+	var ov1;
+	var ov2;
+	var ov3;
+	var ov4;
+	var ov5;
+	var ov6;
+	var ov7;
+	var ov8;
+	var ov9;
+	var sh;
+	var s0;
+	var s1;
+	var s2;
+	var s3;
+	var s4;
+	var s5;
+	var s6;
+	var s7;
+	var s8;
+	var s9;
+	var sv;
+	var ov;
+	var iv;
+	var i0;
+	var i1;
+	var i2;
+	var i3;
+	var i4;
+	var i5;
+	var i6;
+	var i7;
+	var i8;
+	var i9;
+	var j0;
+	var j1;
+	var j2;
+	var j3;
+	var j4;
+	var j5;
+	var j6;
+	var j7;
+	var j8;
+	var j9;
+	var N;
+	var x;
+	var y;
+	var z;
+	var v;
+	var o;
+	var k;
+
+	// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...
+
+	N = arrays.length;
+	x = arrays[ 0 ];
+	y = arrays[ 1 ];
+	z = arrays[ 2 ];
+
+	// Resolve the loop interchange order:
+	o = loopOrder( shape, stridesX, stridesY, stridesZ );
+	sh = o.sh;
+	sv = [ o.sx, o.sy, o.sz ];
+	for ( k = 3; k < N; k++ ) {
+		sv.push( takeIndexed( arrays[k].strides, o.idx ) );
+	}
+	// Determine the block size:
+	bsize = blockSize( x.dtype, y.dtype, z.dtype );
+
+	// Resolve a list of pointers to the first indexed elements in the respective ndarrays:
+	ov = offsets( arrays );
+
+	// Cache offset increments for the innermost loop...
+	dv0 = [];
+	for ( k = 0; k < N; k++ ) {
+		dv0.push( sv[k][0] );
+	}
+	// Initialize loop variables...
+	ov1 = zeros( N );
+	ov2 = zeros( N );
+	ov3 = zeros( N );
+	ov4 = zeros( N );
+	ov5 = zeros( N );
+	ov6 = zeros( N );
+	ov7 = zeros( N );
+	ov8 = zeros( N );
+	ov9 = zeros( N );
+	dv1 = zeros( N );
+	dv2 = zeros( N );
+	dv3 = zeros( N );
+	dv4 = zeros( N );
+	dv5 = zeros( N );
+	dv6 = zeros( N );
+	dv7 = zeros( N );
+	dv8 = zeros( N );
+	dv9 = zeros( N );
+	iv = zeros( N );
+
+	// 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 blocks...
+	for ( j9 = sh[9]; j9 > 0; ) {
+		if ( j9 < bsize ) {
+			s9 = j9;
+			j9 = 0;
+		} else {
+			s9 = bsize;
+			j9 -= bsize;
+		}
+		for ( k = 0; k < N; k++ ) {
+			ov9[ k ] = ov[k] + ( j9*sv[k][9] );
+		}
+		for ( j8 = sh[8]; j8 > 0; ) {
+			if ( j8 < bsize ) {
+				s8 = j8;
+				j8 = 0;
+			} else {
+				s8 = bsize;
+				j8 -= bsize;
+			}
+			for ( k = 0; k < N; k++ ) {
+				dv9[ k ] = sv[k][9] - ( s8*sv[k][8] );
+				ov8[ k ] = ov9[k] + ( j8*sv[k][8] );
+			}
+			for ( j7 = sh[7]; j7 > 0; ) {
+				if ( j7 < bsize ) {
+					s7 = j7;
+					j7 = 0;
+				} else {
+					s7 = bsize;
+					j7 -= bsize;
+				}
+				for ( k = 0; k < N; k++ ) {
+					dv8[ k ] = sv[k][8] - ( s7*sv[k][7] );
+					ov7[ k ] = ov8[k] + ( j7*sv[k][7] );
+				}
+				for ( j6 = sh[6]; j6 > 0; ) {
+					if ( j6 < bsize ) {
+						s6 = j6;
+						j6 = 0;
+					} else {
+						s6 = bsize;
+						j6 -= bsize;
+					}
+					for ( k = 0; k < N; k++ ) {
+						dv7[ k ] = sv[k][7] - ( s6*sv[k][6] );
+						ov6[ k ] = ov7[k] + ( j6*sv[k][6] );
+					}
+					for ( j5 = sh[5]; j5 > 0; ) {
+						if ( j5 < bsize ) {
+							s5 = j5;
+							j5 = 0;
+						} else {
+							s5 = bsize;
+							j5 -= bsize;
+						}
+						for ( k = 0; k < N; k++ ) {
+							dv6[ k ] = sv[k][6] - ( s5*sv[k][5] );
+							ov5[ k ] = ov6[k] + ( j5*sv[k][5] );
+						}
+						for ( j4 = sh[4]; j4 > 0; ) {
+							if ( j4 < bsize ) {
+								s4 = j4;
+								j4 = 0;
+							} else {
+								s4 = bsize;
+								j4 -= bsize;
+							}
+							for ( k = 0; k < N; k++ ) {
+								dv5[ k ] = sv[k][5] - ( s4*sv[k][4] );
+								ov4[ k ] = ov5[k] + ( j4*sv[k][4] );
+							}
+							for ( j3 = sh[3]; j3 > 0; ) {
+								if ( j3 < bsize ) {
+									s3 = j3;
+									j3 = 0;
+								} else {
+									s3 = bsize;
+									j3 -= bsize;
+								}
+								for ( k = 0; k < N; k++ ) {
+									dv4[ k ] = sv[k][4] - ( s3*sv[k][3] );
+									ov3[ k ] = ov4[k] + ( j3*sv[k][3] );
+								}
+								for ( j2 = sh[2]; j2 > 0; ) {
+									if ( j2 < bsize ) {
+										s2 = j2;
+										j2 = 0;
+									} else {
+										s2 = bsize;
+										j2 -= bsize;
+									}
+									for ( k = 0; k < N; k++ ) {
+										dv3[ k ] = sv[k][3] - ( s2*sv[k][2] );
+										ov2[ k ] = ov3[k] + ( j2*sv[k][2] );
+									}
+									for ( j1 = sh[1]; j1 > 0; ) {
+										if ( j1 < bsize ) {
+											s1 = j1;
+											j1 = 0;
+										} else {
+											s1 = bsize;
+											j1 -= bsize;
+										}
+										for ( k = 0; k < N; k++ ) {
+											dv2[ k ] = sv[k][2] - ( s1*sv[k][1] );
+											ov1[ k ] = ov2[k] + ( j1*sv[k][1] );
+										}
+										for ( j0 = sh[0]; j0 > 0; ) {
+											if ( j0 < bsize ) {
+												s0 = j0;
+												j0 = 0;
+											} else {
+												s0 = bsize;
+												j0 -= bsize;
+											}
+											// Compute index offsets and loop offset increments for the first ndarray elements in the current block...
+											for ( k = 0; k < N; k++ ) {
+												iv[ k ] = ov1[k] + ( j0*sv[k][0] );
+												dv1[ k ] = sv[k][1] - ( s0*sv[k][0] );
+											}
+											// 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/blocked/lib/2d.js b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/lib/2d.js
new file mode 100644
index 000000000000..9294b2b486bf
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/lib/2d.js
@@ -0,0 +1,247 @@
+/**
+* @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 loopOrder = require( '@stdlib/ndarray/base/binary-loop-interchange-order' );
+var blockSize = require( '@stdlib/ndarray/base/binary-tiling-block-size' );
+var takeIndexed = require( '@stdlib/array/base/take-indexed' );
+var copyIndexed = require( '@stdlib/array/base/copy-indexed' );
+var zeros = require( '@stdlib/array/base/zeros' );
+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 via loop blocking.
+*
+* @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' );
+* var strategy = require( '@stdlib/ndarray/base/kernels/generic/unary-strided1d/strategy' );
+*
+* // 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 input/output strategies for iterating over subarray views:
+* var strategyX = strategy( views[ 0 ] );
+* var strategyY = strategy( views[ 1 ] );
+* var strategyZ = strategy( views[ 2 ] );
+*
+* // Apply strided function:
+* kernel( gwxpy, [ x, y, z ], views, [ 1, 3 ], [ 12, 4 ], [ 12, 4 ], [ 12, 4 ], strategyX, strategyY, strategyZ, {} );
+*
+* 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 bsize;
+	var dv0;
+	var dv1;
+	var ov1;
+	var sh;
+	var s0;
+	var s1;
+	var sv;
+	var ov;
+	var iv;
+	var i0;
+	var i1;
+	var j0;
+	var j1;
+	var N;
+	var x;
+	var y;
+	var z;
+	var v;
+	var o;
+	var k;
+
+	// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...
+
+	N = arrays.length;
+	x = arrays[ 0 ];
+	y = arrays[ 1 ];
+	z = arrays[ 2 ];
+
+	// Resolve the loop interchange order:
+	o = loopOrder( shape, stridesX, stridesY, stridesZ );
+	sh = o.sh;
+	sv = [ o.sx, o.sy, o.sz ];
+	for ( k = 3; k < N; k++ ) {
+		sv.push( takeIndexed( arrays[k].strides, o.idx ) );
+	}
+	// Determine the block size:
+	bsize = blockSize( x.dtype, y.dtype, z.dtype );
+
+	// Resolve a list of pointers to the first indexed elements in the respective ndarrays:
+	ov = offsets( arrays );
+
+	// Cache offset increments for the innermost loop...
+	dv0 = [];
+	for ( k = 0; k < N; k++ ) {
+		dv0.push( sv[k][0] );
+	}
+	// Initialize loop variables...
+	ov1 = zeros( N );
+	dv1 = zeros( N );
+	iv = zeros( N );
+
+	// 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 blocks...
+	for ( j1 = sh[1]; j1 > 0; ) {
+		if ( j1 < bsize ) {
+			s1 = j1;
+			j1 = 0;
+		} else {
+			s1 = bsize;
+			j1 -= bsize;
+		}
+		for ( k = 0; k < N; k++ ) {
+			ov1[ k ] = ov[k] + ( j1*sv[k][1] );
+		}
+		for ( j0 = sh[0]; j0 > 0; ) {
+			if ( j0 < bsize ) {
+				s0 = j0;
+				j0 = 0;
+			} else {
+				s0 = bsize;
+				j0 -= bsize;
+			}
+			// Compute index offsets and loop offset increments for the first ndarray elements in the current block...
+			for ( k = 0; k < N; k++ ) {
+				iv[ k ] = ov1[k] + ( j0*sv[k][0] );
+				dv1[ k ] = sv[k][1] - ( s0*sv[k][0] );
+			}
+			// 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/blocked/lib/3d.js b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/lib/3d.js
new file mode 100644
index 000000000000..f16bd91e9686
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/lib/3d.js
@@ -0,0 +1,272 @@
+/**
+* @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 loopOrder = require( '@stdlib/ndarray/base/binary-loop-interchange-order' );
+var blockSize = require( '@stdlib/ndarray/base/binary-tiling-block-size' );
+var takeIndexed = require( '@stdlib/array/base/take-indexed' );
+var copyIndexed = require( '@stdlib/array/base/copy-indexed' );
+var zeros = require( '@stdlib/array/base/zeros' );
+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 via loop blocking.
+*
+* @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' );
+* var strategy = require( '@stdlib/ndarray/base/kernels/generic/unary-strided1d/strategy' );
+*
+* // 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 input/output strategies for iterating over subarray views:
+* var strategyX = strategy( views[ 0 ] );
+* var strategyY = strategy( views[ 1 ] );
+* var strategyZ = strategy( views[ 2 ] );
+*
+* // Apply strided function:
+* kernel( gwxpy, [ x, y, z ], views, [ 1, 1, 3 ], [ 12, 12, 4 ], [ 12, 12, 4 ], [ 12, 12, 4 ], strategyX, strategyY, strategyZ, {} );
+*
+* 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 bsize;
+	var dv0;
+	var dv1;
+	var dv2;
+	var ov1;
+	var ov2;
+	var sh;
+	var s0;
+	var s1;
+	var s2;
+	var sv;
+	var ov;
+	var iv;
+	var i0;
+	var i1;
+	var i2;
+	var j0;
+	var j1;
+	var j2;
+	var N;
+	var x;
+	var y;
+	var z;
+	var v;
+	var o;
+	var k;
+
+	// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...
+
+	N = arrays.length;
+	x = arrays[ 0 ];
+	y = arrays[ 1 ];
+	z = arrays[ 2 ];
+
+	// Resolve the loop interchange order:
+	o = loopOrder( shape, stridesX, stridesY, stridesZ );
+	sh = o.sh;
+	sv = [ o.sx, o.sy, o.sz ];
+	for ( k = 3; k < N; k++ ) {
+		sv.push( takeIndexed( arrays[k].strides, o.idx ) );
+	}
+	// Determine the block size:
+	bsize = blockSize( x.dtype, y.dtype, z.dtype );
+
+	// Resolve a list of pointers to the first indexed elements in the respective ndarrays:
+	ov = offsets( arrays );
+
+	// Cache offset increments for the innermost loop...
+	dv0 = [];
+	for ( k = 0; k < N; k++ ) {
+		dv0.push( sv[k][0] );
+	}
+	// Initialize loop variables...
+	ov1 = zeros( N );
+	ov2 = zeros( N );
+	dv1 = zeros( N );
+	dv2 = zeros( N );
+	iv = zeros( N );
+
+	// 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 blocks...
+	for ( j2 = sh[2]; j2 > 0; ) {
+		if ( j2 < bsize ) {
+			s2 = j2;
+			j2 = 0;
+		} else {
+			s2 = bsize;
+			j2 -= bsize;
+		}
+		for ( k = 0; k < N; k++ ) {
+			ov2[ k ] = ov[k] + ( j2*sv[k][2] );
+		}
+		for ( j1 = sh[1]; j1 > 0; ) {
+			if ( j1 < bsize ) {
+				s1 = j1;
+				j1 = 0;
+			} else {
+				s1 = bsize;
+				j1 -= bsize;
+			}
+			for ( k = 0; k < N; k++ ) {
+				ov1[ k ] = ov2[k] + ( j1*sv[k][1] );
+				dv2[ k ] = sv[k][2] - ( s1*sv[k][1] );
+			}
+			for ( j0 = sh[0]; j0 > 0; ) {
+				if ( j0 < bsize ) {
+					s0 = j0;
+					j0 = 0;
+				} else {
+					s0 = bsize;
+					j0 -= bsize;
+				}
+				// Compute index offsets and loop offset increments for the first ndarray elements in the current block...
+				for ( k = 0; k < N; k++ ) {
+					iv[ k ] = ov1[k] + ( j0*sv[k][0] );
+					dv1[ k ] = sv[k][1] - ( s0*sv[k][0] );
+				}
+				// 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/blocked/lib/4d.js b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/lib/4d.js
new file mode 100644
index 000000000000..6f7781f6717f
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/lib/4d.js
@@ -0,0 +1,295 @@
+/**
+* @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 loopOrder = require( '@stdlib/ndarray/base/binary-loop-interchange-order' );
+var blockSize = require( '@stdlib/ndarray/base/binary-tiling-block-size' );
+var takeIndexed = require( '@stdlib/array/base/take-indexed' );
+var copyIndexed = require( '@stdlib/array/base/copy-indexed' );
+var zeros = require( '@stdlib/array/base/zeros' );
+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 via loop blocking.
+*
+* @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' );
+* var strategy = require( '@stdlib/ndarray/base/kernels/generic/unary-strided1d/strategy' );
+*
+* // 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 input/output strategies for iterating over subarray views:
+* var strategyX = strategy( views[ 0 ] );
+* var strategyY = strategy( views[ 1 ] );
+* var strategyZ = strategy( views[ 2 ] );
+*
+* // 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 ], strategyX, strategyY, strategyZ, {} );
+*
+* 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 bsize;
+	var dv0;
+	var dv1;
+	var dv2;
+	var dv3;
+	var ov1;
+	var ov2;
+	var ov3;
+	var sh;
+	var s0;
+	var s1;
+	var s2;
+	var s3;
+	var sv;
+	var ov;
+	var iv;
+	var i0;
+	var i1;
+	var i2;
+	var i3;
+	var j0;
+	var j1;
+	var j2;
+	var j3;
+	var N;
+	var x;
+	var y;
+	var z;
+	var v;
+	var o;
+	var k;
+
+	// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...
+
+	N = arrays.length;
+	x = arrays[ 0 ];
+	y = arrays[ 1 ];
+	z = arrays[ 2 ];
+
+	// Resolve the loop interchange order:
+	o = loopOrder( shape, stridesX, stridesY, stridesZ );
+	sh = o.sh;
+	sv = [ o.sx, o.sy, o.sz ];
+	for ( k = 3; k < N; k++ ) {
+		sv.push( takeIndexed( arrays[k].strides, o.idx ) );
+	}
+	// Determine the block size:
+	bsize = blockSize( x.dtype, y.dtype, z.dtype );
+
+	// Resolve a list of pointers to the first indexed elements in the respective ndarrays:
+	ov = offsets( arrays );
+
+	// Cache offset increments for the innermost loop...
+	dv0 = [];
+	for ( k = 0; k < N; k++ ) {
+		dv0.push( sv[k][0] );
+	}
+	// Initialize loop variables...
+	ov1 = zeros( N );
+	ov2 = zeros( N );
+	ov3 = zeros( N );
+	dv1 = zeros( N );
+	dv2 = zeros( N );
+	dv3 = zeros( N );
+	iv = zeros( N );
+
+	// 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 blocks...
+	for ( j3 = sh[3]; j3 > 0; ) {
+		if ( j3 < bsize ) {
+			s3 = j3;
+			j3 = 0;
+		} else {
+			s3 = bsize;
+			j3 -= bsize;
+		}
+		for ( k = 0; k < N; k++ ) {
+			ov3[ k ] = ov[k] + ( j3*sv[k][3] );
+		}
+		for ( j2 = sh[2]; j2 > 0; ) {
+			if ( j2 < bsize ) {
+				s2 = j2;
+				j2 = 0;
+			} else {
+				s2 = bsize;
+				j2 -= bsize;
+			}
+			for ( k = 0; k < N; k++ ) {
+				ov2[ k ] = ov3[k] + ( j2*sv[k][2] );
+				dv3[ k ] = sv[k][3] - ( s2*sv[k][2] );
+			}
+			for ( j1 = sh[1]; j1 > 0; ) {
+				if ( j1 < bsize ) {
+					s1 = j1;
+					j1 = 0;
+				} else {
+					s1 = bsize;
+					j1 -= bsize;
+				}
+				for ( k = 0; k < N; k++ ) {
+					ov1[ k ] = ov2[k] + ( j1*sv[k][1] );
+					dv2[ k ] = sv[k][2] - ( s1*sv[k][1] );
+				}
+				for ( j0 = sh[0]; j0 > 0; ) {
+					if ( j0 < bsize ) {
+						s0 = j0;
+						j0 = 0;
+					} else {
+						s0 = bsize;
+						j0 -= bsize;
+					}
+					// Compute index offsets and loop offset increments for the first ndarray elements in the current block...
+					for ( k = 0; k < N; k++ ) {
+						iv[ k ] = ov1[k] + ( j0*sv[k][0] );
+						dv1[ k ] = sv[k][1] - ( s0*sv[k][0] );
+					}
+					// 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/blocked/lib/5d.js b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/lib/5d.js
new file mode 100644
index 000000000000..7541910d1c87
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/lib/5d.js
@@ -0,0 +1,318 @@
+/**
+* @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 loopOrder = require( '@stdlib/ndarray/base/binary-loop-interchange-order' );
+var blockSize = require( '@stdlib/ndarray/base/binary-tiling-block-size' );
+var takeIndexed = require( '@stdlib/array/base/take-indexed' );
+var copyIndexed = require( '@stdlib/array/base/copy-indexed' );
+var zeros = require( '@stdlib/array/base/zeros' );
+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 via loop blocking.
+*
+* @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' );
+* var strategy = require( '@stdlib/ndarray/base/kernels/generic/unary-strided1d/strategy' );
+*
+* // 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 input/output strategies for iterating over subarray views:
+* var strategyX = strategy( views[ 0 ] );
+* var strategyY = strategy( views[ 1 ] );
+* var strategyZ = strategy( views[ 2 ] );
+*
+* // 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 ], strategyX, strategyY, strategyZ, {} );
+*
+* 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 bsize;
+	var dv0;
+	var dv1;
+	var dv2;
+	var dv3;
+	var dv4;
+	var ov1;
+	var ov2;
+	var ov3;
+	var ov4;
+	var sh;
+	var s0;
+	var s1;
+	var s2;
+	var s3;
+	var s4;
+	var sv;
+	var ov;
+	var iv;
+	var i0;
+	var i1;
+	var i2;
+	var i3;
+	var i4;
+	var j0;
+	var j1;
+	var j2;
+	var j3;
+	var j4;
+	var N;
+	var x;
+	var y;
+	var z;
+	var v;
+	var o;
+	var k;
+
+	// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...
+
+	N = arrays.length;
+	x = arrays[ 0 ];
+	y = arrays[ 1 ];
+	z = arrays[ 2 ];
+
+	// Resolve the loop interchange order:
+	o = loopOrder( shape, stridesX, stridesY, stridesZ );
+	sh = o.sh;
+	sv = [ o.sx, o.sy, o.sz ];
+	for ( k = 3; k < N; k++ ) {
+		sv.push( takeIndexed( arrays[k].strides, o.idx ) );
+	}
+	// Determine the block size:
+	bsize = blockSize( x.dtype, y.dtype, z.dtype );
+
+	// Resolve a list of pointers to the first indexed elements in the respective ndarrays:
+	ov = offsets( arrays );
+
+	// Cache offset increments for the innermost loop...
+	dv0 = [];
+	for ( k = 0; k < N; k++ ) {
+		dv0.push( sv[k][0] );
+	}
+	// Initialize loop variables...
+	ov1 = zeros( N );
+	ov2 = zeros( N );
+	ov3 = zeros( N );
+	ov4 = zeros( N );
+	dv1 = zeros( N );
+	dv2 = zeros( N );
+	dv3 = zeros( N );
+	dv4 = zeros( N );
+	iv = zeros( N );
+
+	// 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 blocks...
+	for ( j4 = sh[4]; j4 > 0; ) {
+		if ( j4 < bsize ) {
+			s4 = j4;
+			j4 = 0;
+		} else {
+			s4 = bsize;
+			j4 -= bsize;
+		}
+		for ( k = 0; k < N; k++ ) {
+			ov4[ k ] = ov[k] + ( j4*sv[k][4] );
+		}
+		for ( j3 = sh[3]; j3 > 0; ) {
+			if ( j3 < bsize ) {
+				s3 = j3;
+				j3 = 0;
+			} else {
+				s3 = bsize;
+				j3 -= bsize;
+			}
+			for ( k = 0; k < N; k++ ) {
+				dv4[ k ] = sv[k][4] - ( s3*sv[k][3] );
+				ov3[ k ] = ov4[k] + ( j3*sv[k][3] );
+			}
+			for ( j2 = sh[2]; j2 > 0; ) {
+				if ( j2 < bsize ) {
+					s2 = j2;
+					j2 = 0;
+				} else {
+					s2 = bsize;
+					j2 -= bsize;
+				}
+				for ( k = 0; k < N; k++ ) {
+					dv3[ k ] = sv[k][3] - ( s2*sv[k][2] );
+					ov2[ k ] = ov3[k] + ( j2*sv[k][2] );
+				}
+				for ( j1 = sh[1]; j1 > 0; ) {
+					if ( j1 < bsize ) {
+						s1 = j1;
+						j1 = 0;
+					} else {
+						s1 = bsize;
+						j1 -= bsize;
+					}
+					for ( k = 0; k < N; k++ ) {
+						dv2[ k ] = sv[k][2] - ( s1*sv[k][1] );
+						ov1[ k ] = ov2[k] + ( j1*sv[k][1] );
+					}
+					for ( j0 = sh[0]; j0 > 0; ) {
+						if ( j0 < bsize ) {
+							s0 = j0;
+							j0 = 0;
+						} else {
+							s0 = bsize;
+							j0 -= bsize;
+						}
+						// Compute index offsets and loop offset increments for the first ndarray elements in the current block...
+						for ( k = 0; k < N; k++ ) {
+							iv[ k ] = ov1[k] + ( j0*sv[k][0] );
+							dv1[ k ] = sv[k][1] - ( s0*sv[k][0] );
+						}
+						// 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/blocked/lib/6d.js b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/lib/6d.js
new file mode 100644
index 000000000000..60bd5ca80250
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/lib/6d.js
@@ -0,0 +1,341 @@
+/**
+* @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 loopOrder = require( '@stdlib/ndarray/base/binary-loop-interchange-order' );
+var blockSize = require( '@stdlib/ndarray/base/binary-tiling-block-size' );
+var takeIndexed = require( '@stdlib/array/base/take-indexed' );
+var copyIndexed = require( '@stdlib/array/base/copy-indexed' );
+var zeros = require( '@stdlib/array/base/zeros' );
+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 via loop blocking.
+*
+* @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' );
+* var strategy = require( '@stdlib/ndarray/base/kernels/generic/unary-strided1d/strategy' );
+*
+* // 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 input/output strategies for iterating over subarray views:
+* var strategyX = strategy( views[ 0 ] );
+* var strategyY = strategy( views[ 1 ] );
+* var strategyZ = strategy( views[ 2 ] );
+*
+* // 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 ], strategyX, strategyY, strategyZ, {} );
+*
+* 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 bsize;
+	var dv0;
+	var dv1;
+	var dv2;
+	var dv3;
+	var dv4;
+	var dv5;
+	var ov1;
+	var ov2;
+	var ov3;
+	var ov4;
+	var ov5;
+	var sh;
+	var s0;
+	var s1;
+	var s2;
+	var s3;
+	var s4;
+	var s5;
+	var sv;
+	var ov;
+	var iv;
+	var i0;
+	var i1;
+	var i2;
+	var i3;
+	var i4;
+	var i5;
+	var j0;
+	var j1;
+	var j2;
+	var j3;
+	var j4;
+	var j5;
+	var N;
+	var x;
+	var y;
+	var z;
+	var v;
+	var o;
+	var k;
+
+	// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...
+
+	N = arrays.length;
+	x = arrays[ 0 ];
+	y = arrays[ 1 ];
+	z = arrays[ 2 ];
+
+	// Resolve the loop interchange order:
+	o = loopOrder( shape, stridesX, stridesY, stridesZ );
+	sh = o.sh;
+	sv = [ o.sx, o.sy, o.sz ];
+	for ( k = 3; k < N; k++ ) {
+		sv.push( takeIndexed( arrays[k].strides, o.idx ) );
+	}
+	// Determine the block size:
+	bsize = blockSize( x.dtype, y.dtype, z.dtype );
+
+	// Resolve a list of pointers to the first indexed elements in the respective ndarrays:
+	ov = offsets( arrays );
+
+	// Cache offset increments for the innermost loop...
+	dv0 = [];
+	for ( k = 0; k < N; k++ ) {
+		dv0.push( sv[k][0] );
+	}
+	// Initialize loop variables...
+	ov1 = zeros( N );
+	ov2 = zeros( N );
+	ov3 = zeros( N );
+	ov4 = zeros( N );
+	ov5 = zeros( N );
+	dv1 = zeros( N );
+	dv2 = zeros( N );
+	dv3 = zeros( N );
+	dv4 = zeros( N );
+	dv5 = zeros( N );
+	iv = zeros( N );
+
+	// 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 blocks...
+	for ( j5 = sh[5]; j5 > 0; ) {
+		if ( j5 < bsize ) {
+			s5 = j5;
+			j5 = 0;
+		} else {
+			s5 = bsize;
+			j5 -= bsize;
+		}
+		for ( k = 0; k < N; k++ ) {
+			ov5[ k ] = ov[k] + ( j5*sv[k][5] );
+		}
+		for ( j4 = sh[4]; j4 > 0; ) {
+			if ( j4 < bsize ) {
+				s4 = j4;
+				j4 = 0;
+			} else {
+				s4 = bsize;
+				j4 -= bsize;
+			}
+			for ( k = 0; k < N; k++ ) {
+				dv5[ k ] = sv[k][5] - ( s4*sv[k][4] );
+				ov4[ k ] = ov5[k] + ( j4*sv[k][4] );
+			}
+			for ( j3 = sh[3]; j3 > 0; ) {
+				if ( j3 < bsize ) {
+					s3 = j3;
+					j3 = 0;
+				} else {
+					s3 = bsize;
+					j3 -= bsize;
+				}
+				for ( k = 0; k < N; k++ ) {
+					dv4[ k ] = sv[k][4] - ( s3*sv[k][3] );
+					ov3[ k ] = ov4[k] + ( j3*sv[k][3] );
+				}
+				for ( j2 = sh[2]; j2 > 0; ) {
+					if ( j2 < bsize ) {
+						s2 = j2;
+						j2 = 0;
+					} else {
+						s2 = bsize;
+						j2 -= bsize;
+					}
+					for ( k = 0; k < N; k++ ) {
+						dv3[ k ] = sv[k][3] - ( s2*sv[k][2] );
+						ov2[ k ] = ov3[k] + ( j2*sv[k][2] );
+					}
+					for ( j1 = sh[1]; j1 > 0; ) {
+						if ( j1 < bsize ) {
+							s1 = j1;
+							j1 = 0;
+						} else {
+							s1 = bsize;
+							j1 -= bsize;
+						}
+						for ( k = 0; k < N; k++ ) {
+							dv2[ k ] = sv[k][2] - ( s1*sv[k][1] );
+							ov1[ k ] = ov2[k] + ( j1*sv[k][1] );
+						}
+						for ( j0 = sh[0]; j0 > 0; ) {
+							if ( j0 < bsize ) {
+								s0 = j0;
+								j0 = 0;
+							} else {
+								s0 = bsize;
+								j0 -= bsize;
+							}
+							// Compute index offsets and loop offset increments for the first ndarray elements in the current block...
+							for ( k = 0; k < N; k++ ) {
+								iv[ k ] = ov1[k] + ( j0*sv[k][0] );
+								dv1[ k ] = sv[k][1] - ( s0*sv[k][0] );
+							}
+							// 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/blocked/lib/7d.js b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/lib/7d.js
new file mode 100644
index 000000000000..01652a5c16ac
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/lib/7d.js
@@ -0,0 +1,364 @@
+/**
+* @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 loopOrder = require( '@stdlib/ndarray/base/binary-loop-interchange-order' );
+var blockSize = require( '@stdlib/ndarray/base/binary-tiling-block-size' );
+var takeIndexed = require( '@stdlib/array/base/take-indexed' );
+var copyIndexed = require( '@stdlib/array/base/copy-indexed' );
+var zeros = require( '@stdlib/array/base/zeros' );
+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 via loop blocking.
+*
+* @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' );
+* var strategy = require( '@stdlib/ndarray/base/kernels/generic/unary-strided1d/strategy' );
+*
+* // 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 input/output strategies for iterating over subarray views:
+* var strategyX = strategy( views[ 0 ] );
+* var strategyY = strategy( views[ 1 ] );
+* var strategyZ = strategy( views[ 2 ] );
+*
+* // 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 ], strategyX, strategyY, strategyZ, {} );
+*
+* 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 bsize;
+	var dv0;
+	var dv1;
+	var dv2;
+	var dv3;
+	var dv4;
+	var dv5;
+	var dv6;
+	var ov1;
+	var ov2;
+	var ov3;
+	var ov4;
+	var ov5;
+	var ov6;
+	var sh;
+	var s0;
+	var s1;
+	var s2;
+	var s3;
+	var s4;
+	var s5;
+	var s6;
+	var sv;
+	var ov;
+	var iv;
+	var i0;
+	var i1;
+	var i2;
+	var i3;
+	var i4;
+	var i5;
+	var i6;
+	var j0;
+	var j1;
+	var j2;
+	var j3;
+	var j4;
+	var j5;
+	var j6;
+	var N;
+	var x;
+	var y;
+	var z;
+	var v;
+	var o;
+	var k;
+
+	// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...
+
+	N = arrays.length;
+	x = arrays[ 0 ];
+	y = arrays[ 1 ];
+	z = arrays[ 2 ];
+
+	// Resolve the loop interchange order:
+	o = loopOrder( shape, stridesX, stridesY, stridesZ );
+	sh = o.sh;
+	sv = [ o.sx, o.sy, o.sz ];
+	for ( k = 3; k < N; k++ ) {
+		sv.push( takeIndexed( arrays[k].strides, o.idx ) );
+	}
+	// Determine the block size:
+	bsize = blockSize( x.dtype, y.dtype, z.dtype );
+
+	// Resolve a list of pointers to the first indexed elements in the respective ndarrays:
+	ov = offsets( arrays );
+
+	// Cache offset increments for the innermost loop...
+	dv0 = [];
+	for ( k = 0; k < N; k++ ) {
+		dv0.push( sv[k][0] );
+	}
+	// Initialize loop variables...
+	ov1 = zeros( N );
+	ov2 = zeros( N );
+	ov3 = zeros( N );
+	ov4 = zeros( N );
+	ov5 = zeros( N );
+	ov6 = zeros( N );
+	dv1 = zeros( N );
+	dv2 = zeros( N );
+	dv3 = zeros( N );
+	dv4 = zeros( N );
+	dv5 = zeros( N );
+	dv6 = zeros( N );
+	iv = zeros( N );
+
+	// 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 blocks...
+	for ( j6 = sh[6]; j6 > 0; ) {
+		if ( j6 < bsize ) {
+			s6 = j6;
+			j6 = 0;
+		} else {
+			s6 = bsize;
+			j6 -= bsize;
+		}
+		for ( k = 0; k < N; k++ ) {
+			ov6[ k ] = ov[k] + ( j6*sv[k][6] );
+		}
+		for ( j5 = sh[5]; j5 > 0; ) {
+			if ( j5 < bsize ) {
+				s5 = j5;
+				j5 = 0;
+			} else {
+				s5 = bsize;
+				j5 -= bsize;
+			}
+			for ( k = 0; k < N; k++ ) {
+				dv6[ k ] = sv[k][6] - ( s5*sv[k][5] );
+				ov5[ k ] = ov6[k] + ( j5*sv[k][5] );
+			}
+			for ( j4 = sh[4]; j4 > 0; ) {
+				if ( j4 < bsize ) {
+					s4 = j4;
+					j4 = 0;
+				} else {
+					s4 = bsize;
+					j4 -= bsize;
+				}
+				for ( k = 0; k < N; k++ ) {
+					dv5[ k ] = sv[k][5] - ( s4*sv[k][4] );
+					ov4[ k ] = ov5[k] + ( j4*sv[k][4] );
+				}
+				for ( j3 = sh[3]; j3 > 0; ) {
+					if ( j3 < bsize ) {
+						s3 = j3;
+						j3 = 0;
+					} else {
+						s3 = bsize;
+						j3 -= bsize;
+					}
+					for ( k = 0; k < N; k++ ) {
+						dv4[ k ] = sv[k][4] - ( s3*sv[k][3] );
+						ov3[ k ] = ov4[k] + ( j3*sv[k][3] );
+					}
+					for ( j2 = sh[2]; j2 > 0; ) {
+						if ( j2 < bsize ) {
+							s2 = j2;
+							j2 = 0;
+						} else {
+							s2 = bsize;
+							j2 -= bsize;
+						}
+						for ( k = 0; k < N; k++ ) {
+							dv3[ k ] = sv[k][3] - ( s2*sv[k][2] );
+							ov2[ k ] = ov3[k] + ( j2*sv[k][2] );
+						}
+						for ( j1 = sh[1]; j1 > 0; ) {
+							if ( j1 < bsize ) {
+								s1 = j1;
+								j1 = 0;
+							} else {
+								s1 = bsize;
+								j1 -= bsize;
+							}
+							for ( k = 0; k < N; k++ ) {
+								dv2[ k ] = sv[k][2] - ( s1*sv[k][1] );
+								ov1[ k ] = ov2[k] + ( j1*sv[k][1] );
+							}
+							for ( j0 = sh[0]; j0 > 0; ) {
+								if ( j0 < bsize ) {
+									s0 = j0;
+									j0 = 0;
+								} else {
+									s0 = bsize;
+									j0 -= bsize;
+								}
+								// Compute index offsets and loop offset increments for the first ndarray elements in the current block...
+								for ( k = 0; k < N; k++ ) {
+									iv[ k ] = ov1[k] + ( j0*sv[k][0] );
+									dv1[ k ] = sv[k][1] - ( s0*sv[k][0] );
+								}
+								// 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/blocked/lib/8d.js b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/lib/8d.js
new file mode 100644
index 000000000000..4d6d43b6efc3
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/lib/8d.js
@@ -0,0 +1,387 @@
+/**
+* @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 loopOrder = require( '@stdlib/ndarray/base/binary-loop-interchange-order' );
+var blockSize = require( '@stdlib/ndarray/base/binary-tiling-block-size' );
+var takeIndexed = require( '@stdlib/array/base/take-indexed' );
+var copyIndexed = require( '@stdlib/array/base/copy-indexed' );
+var zeros = require( '@stdlib/array/base/zeros' );
+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 via loop blocking.
+*
+* @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' );
+* var strategy = require( '@stdlib/ndarray/base/kernels/generic/unary-strided1d/strategy' );
+*
+* // 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 input/output strategies for iterating over subarray views:
+* var strategyX = strategy( views[ 0 ] );
+* var strategyY = strategy( views[ 1 ] );
+* var strategyZ = strategy( views[ 2 ] );
+*
+* // 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 ], strategyX, strategyY, strategyZ, {} );
+*
+* 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 bsize;
+	var dv0;
+	var dv1;
+	var dv2;
+	var dv3;
+	var dv4;
+	var dv5;
+	var dv6;
+	var dv7;
+	var ov1;
+	var ov2;
+	var ov3;
+	var ov4;
+	var ov5;
+	var ov6;
+	var ov7;
+	var sh;
+	var s0;
+	var s1;
+	var s2;
+	var s3;
+	var s4;
+	var s5;
+	var s6;
+	var s7;
+	var sv;
+	var ov;
+	var iv;
+	var i0;
+	var i1;
+	var i2;
+	var i3;
+	var i4;
+	var i5;
+	var i6;
+	var i7;
+	var j0;
+	var j1;
+	var j2;
+	var j3;
+	var j4;
+	var j5;
+	var j6;
+	var j7;
+	var N;
+	var x;
+	var y;
+	var z;
+	var v;
+	var o;
+	var k;
+
+	// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...
+
+	N = arrays.length;
+	x = arrays[ 0 ];
+	y = arrays[ 1 ];
+	z = arrays[ 2 ];
+
+	// Resolve the loop interchange order:
+	o = loopOrder( shape, stridesX, stridesY, stridesZ );
+	sh = o.sh;
+	sv = [ o.sx, o.sy, o.sz ];
+	for ( k = 3; k < N; k++ ) {
+		sv.push( takeIndexed( arrays[k].strides, o.idx ) );
+	}
+	// Determine the block size:
+	bsize = blockSize( x.dtype, y.dtype, z.dtype );
+
+	// Resolve a list of pointers to the first indexed elements in the respective ndarrays:
+	ov = offsets( arrays );
+
+	// Cache offset increments for the innermost loop...
+	dv0 = [];
+	for ( k = 0; k < N; k++ ) {
+		dv0.push( sv[k][0] );
+	}
+	// Initialize loop variables...
+	ov1 = zeros( N );
+	ov2 = zeros( N );
+	ov3 = zeros( N );
+	ov4 = zeros( N );
+	ov5 = zeros( N );
+	ov6 = zeros( N );
+	ov7 = zeros( N );
+	dv1 = zeros( N );
+	dv2 = zeros( N );
+	dv3 = zeros( N );
+	dv4 = zeros( N );
+	dv5 = zeros( N );
+	dv6 = zeros( N );
+	dv7 = zeros( N );
+	iv = zeros( N );
+
+	// 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 blocks...
+	for ( j7 = sh[7]; j7 > 0; ) {
+		if ( j7 < bsize ) {
+			s7 = j7;
+			j7 = 0;
+		} else {
+			s7 = bsize;
+			j7 -= bsize;
+		}
+		for ( k = 0; k < N; k++ ) {
+			ov7[ k ] = ov[k] + ( j7*sv[k][7] );
+		}
+		for ( j6 = sh[6]; j6 > 0; ) {
+			if ( j6 < bsize ) {
+				s6 = j6;
+				j6 = 0;
+			} else {
+				s6 = bsize;
+				j6 -= bsize;
+			}
+			for ( k = 0; k < N; k++ ) {
+				dv7[ k ] = sv[k][7] - ( s6*sv[k][6] );
+				ov6[ k ] = ov7[k] + ( j6*sv[k][6] );
+			}
+			for ( j5 = sh[5]; j5 > 0; ) {
+				if ( j5 < bsize ) {
+					s5 = j5;
+					j5 = 0;
+				} else {
+					s5 = bsize;
+					j5 -= bsize;
+				}
+				for ( k = 0; k < N; k++ ) {
+					dv6[ k ] = sv[k][6] - ( s5*sv[k][5] );
+					ov5[ k ] = ov6[k] + ( j5*sv[k][5] );
+				}
+				for ( j4 = sh[4]; j4 > 0; ) {
+					if ( j4 < bsize ) {
+						s4 = j4;
+						j4 = 0;
+					} else {
+						s4 = bsize;
+						j4 -= bsize;
+					}
+					for ( k = 0; k < N; k++ ) {
+						dv5[ k ] = sv[k][5] - ( s4*sv[k][4] );
+						ov4[ k ] = ov5[k] + ( j4*sv[k][4] );
+					}
+					for ( j3 = sh[3]; j3 > 0; ) {
+						if ( j3 < bsize ) {
+							s3 = j3;
+							j3 = 0;
+						} else {
+							s3 = bsize;
+							j3 -= bsize;
+						}
+						for ( k = 0; k < N; k++ ) {
+							dv4[ k ] = sv[k][4] - ( s3*sv[k][3] );
+							ov3[ k ] = ov4[k] + ( j3*sv[k][3] );
+						}
+						for ( j2 = sh[2]; j2 > 0; ) {
+							if ( j2 < bsize ) {
+								s2 = j2;
+								j2 = 0;
+							} else {
+								s2 = bsize;
+								j2 -= bsize;
+							}
+							for ( k = 0; k < N; k++ ) {
+								dv3[ k ] = sv[k][3] - ( s2*sv[k][2] );
+								ov2[ k ] = ov3[k] + ( j2*sv[k][2] );
+							}
+							for ( j1 = sh[1]; j1 > 0; ) {
+								if ( j1 < bsize ) {
+									s1 = j1;
+									j1 = 0;
+								} else {
+									s1 = bsize;
+									j1 -= bsize;
+								}
+								for ( k = 0; k < N; k++ ) {
+									dv2[ k ] = sv[k][2] - ( s1*sv[k][1] );
+									ov1[ k ] = ov2[k] + ( j1*sv[k][1] );
+								}
+								for ( j0 = sh[0]; j0 > 0; ) {
+									if ( j0 < bsize ) {
+										s0 = j0;
+										j0 = 0;
+									} else {
+										s0 = bsize;
+										j0 -= bsize;
+									}
+									// Compute index offsets and loop offset increments for the first ndarray elements in the current block...
+									for ( k = 0; k < N; k++ ) {
+										iv[ k ] = ov1[k] + ( j0*sv[k][0] );
+										dv1[ k ] = sv[k][1] - ( s0*sv[k][0] );
+									}
+									// 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/blocked/lib/9d.js b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/lib/9d.js
new file mode 100644
index 000000000000..2bff36b204eb
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/lib/9d.js
@@ -0,0 +1,410 @@
+/**
+* @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 loopOrder = require( '@stdlib/ndarray/base/binary-loop-interchange-order' );
+var blockSize = require( '@stdlib/ndarray/base/binary-tiling-block-size' );
+var takeIndexed = require( '@stdlib/array/base/take-indexed' );
+var copyIndexed = require( '@stdlib/array/base/copy-indexed' );
+var zeros = require( '@stdlib/array/base/zeros' );
+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 via loop blocking.
+*
+* @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' );
+* var strategy = require( '@stdlib/ndarray/base/kernels/generic/unary-strided1d/strategy' );
+*
+* // 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 input/output strategies for iterating over subarray views:
+* var strategyX = strategy( views[ 0 ] );
+* var strategyY = strategy( views[ 1 ] );
+* var strategyZ = strategy( views[ 2 ] );
+*
+* // 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 ], strategyX, strategyY, strategyZ, {} );
+*
+* 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 bsize;
+	var dv0;
+	var dv1;
+	var dv2;
+	var dv3;
+	var dv4;
+	var dv5;
+	var dv6;
+	var dv7;
+	var dv8;
+	var ov1;
+	var ov2;
+	var ov3;
+	var ov4;
+	var ov5;
+	var ov6;
+	var ov7;
+	var ov8;
+	var sh;
+	var s0;
+	var s1;
+	var s2;
+	var s3;
+	var s4;
+	var s5;
+	var s6;
+	var s7;
+	var s8;
+	var sv;
+	var ov;
+	var iv;
+	var i0;
+	var i1;
+	var i2;
+	var i3;
+	var i4;
+	var i5;
+	var i6;
+	var i7;
+	var i8;
+	var j0;
+	var j1;
+	var j2;
+	var j3;
+	var j4;
+	var j5;
+	var j6;
+	var j7;
+	var j8;
+	var N;
+	var x;
+	var y;
+	var z;
+	var v;
+	var o;
+	var k;
+
+	// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...
+
+	N = arrays.length;
+	x = arrays[ 0 ];
+	y = arrays[ 1 ];
+	z = arrays[ 2 ];
+
+	// Resolve the loop interchange order:
+	o = loopOrder( shape, stridesX, stridesY, stridesZ );
+	sh = o.sh;
+	sv = [ o.sx, o.sy, o.sz ];
+	for ( k = 3; k < N; k++ ) {
+		sv.push( takeIndexed( arrays[k].strides, o.idx ) );
+	}
+	// Determine the block size:
+	bsize = blockSize( x.dtype, y.dtype, z.dtype );
+
+	// Resolve a list of pointers to the first indexed elements in the respective ndarrays:
+	ov = offsets( arrays );
+
+	// Cache offset increments for the innermost loop...
+	dv0 = [];
+	for ( k = 0; k < N; k++ ) {
+		dv0.push( sv[k][0] );
+	}
+	// Initialize loop variables...
+	ov1 = zeros( N );
+	ov2 = zeros( N );
+	ov3 = zeros( N );
+	ov4 = zeros( N );
+	ov5 = zeros( N );
+	ov6 = zeros( N );
+	ov7 = zeros( N );
+	ov8 = zeros( N );
+	dv1 = zeros( N );
+	dv2 = zeros( N );
+	dv3 = zeros( N );
+	dv4 = zeros( N );
+	dv5 = zeros( N );
+	dv6 = zeros( N );
+	dv7 = zeros( N );
+	dv8 = zeros( N );
+	iv = zeros( N );
+
+	// 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 blocks...
+	for ( j8 = sh[8]; j8 > 0; ) {
+		if ( j8 < bsize ) {
+			s8 = j8;
+			j8 = 0;
+		} else {
+			s8 = bsize;
+			j8 -= bsize;
+		}
+		for ( k = 0; k < N; k++ ) {
+			ov8[ k ] = ov[k] + ( j8*sv[k][8] );
+		}
+		for ( j7 = sh[7]; j7 > 0; ) {
+			if ( j7 < bsize ) {
+				s7 = j7;
+				j7 = 0;
+			} else {
+				s7 = bsize;
+				j7 -= bsize;
+			}
+			for ( k = 0; k < N; k++ ) {
+				dv8[ k ] = sv[k][8] - ( s7*sv[k][7] );
+				ov7[ k ] = ov8[k] + ( j7*sv[k][7] );
+			}
+			for ( j6 = sh[6]; j6 > 0; ) {
+				if ( j6 < bsize ) {
+					s6 = j6;
+					j6 = 0;
+				} else {
+					s6 = bsize;
+					j6 -= bsize;
+				}
+				for ( k = 0; k < N; k++ ) {
+					dv7[ k ] = sv[k][7] - ( s6*sv[k][6] );
+					ov6[ k ] = ov7[k] + ( j6*sv[k][6] );
+				}
+				for ( j5 = sh[5]; j5 > 0; ) {
+					if ( j5 < bsize ) {
+						s5 = j5;
+						j5 = 0;
+					} else {
+						s5 = bsize;
+						j5 -= bsize;
+					}
+					for ( k = 0; k < N; k++ ) {
+						dv6[ k ] = sv[k][6] - ( s5*sv[k][5] );
+						ov5[ k ] = ov6[k] + ( j5*sv[k][5] );
+					}
+					for ( j4 = sh[4]; j4 > 0; ) {
+						if ( j4 < bsize ) {
+							s4 = j4;
+							j4 = 0;
+						} else {
+							s4 = bsize;
+							j4 -= bsize;
+						}
+						for ( k = 0; k < N; k++ ) {
+							dv5[ k ] = sv[k][5] - ( s4*sv[k][4] );
+							ov4[ k ] = ov5[k] + ( j4*sv[k][4] );
+						}
+						for ( j3 = sh[3]; j3 > 0; ) {
+							if ( j3 < bsize ) {
+								s3 = j3;
+								j3 = 0;
+							} else {
+								s3 = bsize;
+								j3 -= bsize;
+							}
+							for ( k = 0; k < N; k++ ) {
+								dv4[ k ] = sv[k][4] - ( s3*sv[k][3] );
+								ov3[ k ] = ov4[k] + ( j3*sv[k][3] );
+							}
+							for ( j2 = sh[2]; j2 > 0; ) {
+								if ( j2 < bsize ) {
+									s2 = j2;
+									j2 = 0;
+								} else {
+									s2 = bsize;
+									j2 -= bsize;
+								}
+								for ( k = 0; k < N; k++ ) {
+									dv3[ k ] = sv[k][3] - ( s2*sv[k][2] );
+									ov2[ k ] = ov3[k] + ( j2*sv[k][2] );
+								}
+								for ( j1 = sh[1]; j1 > 0; ) {
+									if ( j1 < bsize ) {
+										s1 = j1;
+										j1 = 0;
+									} else {
+										s1 = bsize;
+										j1 -= bsize;
+									}
+									for ( k = 0; k < N; k++ ) {
+										dv2[ k ] = sv[k][2] - ( s1*sv[k][1] );
+										ov1[ k ] = ov2[k] + ( j1*sv[k][1] );
+									}
+									for ( j0 = sh[0]; j0 > 0; ) {
+										if ( j0 < bsize ) {
+											s0 = j0;
+											j0 = 0;
+										} else {
+											s0 = bsize;
+											j0 -= bsize;
+										}
+										// Compute index offsets and loop offset increments for the first ndarray elements in the current block...
+										for ( k = 0; k < N; k++ ) {
+											iv[ k ] = ov1[k] + ( j0*sv[k][0] );
+											dv1[ k ] = sv[k][1] - ( s0*sv[k][0] );
+										}
+										// 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/blocked/lib/index.js b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/lib/index.js
new file mode 100644
index 000000000000..a398c4421a8b
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/lib/index.js
@@ -0,0 +1,155 @@
+/**
+* @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 using loop blocking.
+*
+* @module @stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked
+*
+* @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 strategy = require( '@stdlib/ndarray/base/kernels/generic/unary-strided1d/strategy' );
+* var kernel = require( '@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked' );
+*
+* // 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 input/output strategies for 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( 2 );
+*
+* // Apply strided function:
+* f( gwxpy, [ x, y, z ], views, [ 1, 3 ], [ 12, 4 ], [ 12, 4 ], [ 12, 4 ], strategyX, strategyY, strategyZ, {} );
+*
+* 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 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, '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/blocked/lib/main.js b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/lib/main.js
new file mode 100644
index 000000000000..431ccefd098a
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/lib/main.js
@@ -0,0 +1,165 @@
+/**
+* @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 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 = [
+	kernel2d, // 0
+	kernel3d,
+	kernel4d,
+	kernel5d,
+	kernel6d,
+	kernel7d,
+	kernel8d,
+	kernel9d,
+	kernel10d // 8
+];
+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 using loop blocking.
+*
+* @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' );
+* var strategy = require( '@stdlib/ndarray/base/kernels/generic/unary-strided1d/strategy' );
+*
+* // 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 input/output strategies for 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( 2 );
+*
+* // Apply strided function:
+* f( gwxpy, [ x, y, z ], views, [ 1, 3 ], [ 12, 4 ], [ 12, 4 ], [ 12, 4 ], strategyX, strategyY, strategyZ, {} );
+*
+* 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 < 2 || ndims > MAX_DIMS ) {
+		return null;
+	}
+	return KERNELS[ ndims-2 ];
+}
+
+
+// EXPORTS //
+
+module.exports = kernel;
diff --git a/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/package.json b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/package.json
new file mode 100644
index 000000000000..51af24180b29
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/package.json
@@ -0,0 +1,66 @@
+{
+  "name": "@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked",
+  "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 using loop blocking.",
+  "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",
+    "blocked"
+  ],
+  "__stdlib__": {}
+}
diff --git a/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/test/test.js b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/test/test.js
new file mode 100644
index 000000000000..053851cfb7f7
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/kernels/generic/binary-strided1d/blocked/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