feat: add blas/base/dsymm

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stdlib-js · ShabiShett07 · Jun 17, 2025 · Jun 17, 2025 · Jun 17, 2025 · Jun 17, 2025
commit c247a67acb7b6ba3fc5b1096b203f36f095818d2
diff --git a/lib/node_modules/@stdlib/blas/base/dsymm/README.md b/lib/node_modules/@stdlib/blas/base/dsymm/README.md
@@ -0,0 +1,259 @@
+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2024 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.
+
+-->
+
+# dsymm
+
+> Perform the matrix-matrix operation `C = α*A*B + β*C` or `C = α*B*A + β*C` where `α` and `β` are scalars, `A` is a symmetric matrix and `B` and `C` are `M` by `N` matrices.
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var dsymm = require( '@stdlib/blas/base/dsymm' );
+```
+
+#### dsymm( ord, side, uplo, M, N, α, A, lda, B, ldb, β, C, ldc )
+
+Performs the matrix-matrix operation `C = α*A*B + β*C` or `C = α*B*A + β*C` where `α` and `β` are scalars, `A` is a symmetric matrix and `B` and `C` are `M` by `N` matrices.
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+var A = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 2.0, 1.0, 1.0, 1.0, 3.0 ] );
+var B = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );
+var C = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );
+
+dsymm( 'row-major', 'left', 'lower', 3, 3, 1.0, A, 3, B, 3, 1.0, C, 3 );
+// C => <Float64Array>[ 4.0, 4.0, 4.0, 5.0, 5.0, 5.0, 6.0, 6.0, 6.0 ]
+```
+
+The function has the following parameters:
+
+-   **ord**: storage layout.
+-   **side**: specifies whether `A` appears on the left or right of `B`.
+-   **uplo**: specifies whether the upper or lower triangular part of the symmetric matrix `A` is supplied.
+-   **M**: number of rows in the matrix `op(A)` and in the matrix `C`.
+-   **N**: number of columns in the matrix `op(B)` and in the matrix `C`.
+-   **α**: scalar constant.
+-   **A**: first input matrix stored in linear memory as a [`Float64Array`][mdn-float64array].
+-   **lda**: stride of the first dimension of `A` (leading dimension of `A`).
+-   **B**: second input matrix stored in linear memory as a [`Float64Array`][mdn-float64array].
+-   **ldb**: stride of the first dimension of `B` (leading dimension of `B`).
+-   **β**: scalar con
F438
stant
+-   **C**: third input matrix stored in linear memory as a [`Float64Array`][mdn-float64array].
+-   **ldc**: stride of the first dimension of `C` (leading dimension of `C`).
+
+The stride parameters determine how elements in the input arrays are accessed at runtime. For example, to perform matrix multiplication of two subarrays
+
+<!-- eslint-disable max-len -->
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+var A = new Float64Array( [ 1.0, 1.0, 1.0, 0.0, 0.0, 0.0, 1.0, 2.0, 1.0, 0.0, 0.0, 0.0, 1.0, 1.0, 3.0, 0.0, 0.0, 0.0 ] );
+var B = new Float64Array( [ 1.0, 1.0, 1.0, 0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.0 ] );
+var C = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );
+
+dsymm( 'row-major', 'left', 'lower', 3, 3, 1.0, A, 6, B, 6, 1.0, C, 3 );
+// C => <Float64Array>[ 4.0, 4.0, 4.0, 5.0, 5.0, 5.0, 6.0, 6.0, 6.0 ]
+```
+
+<!-- lint disable maximum-heading-length -->
+
+#### dsymm.ndarray( side, uplo, M, N, α, A, sa1, sa2, oa, B, sb1, sb2, ob, β, C, sc1, sc2, oc )
+
+Performs the matrix-matrix operation `C = α*A*B + β*C` or `C = α*B*A + β*C` using alternative indexing semantics and where `α` and `β` are scalars, `A` is a symmetric matrix and `B` and `C` are `M` by `N` matrices.
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+var A = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 2.0, 1.0, 1.0, 1.0, 3.0 ] );
+var B = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );
+var C = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );
+
+dsymm( 'left', 'lower', 3, 3, 1.0, A, 3, 1, 0, B, 3, 1, 0, 1.0, C, 3, 1, 0 );
+// C => <Float64Array>[ 4.0, 4.0, 4.0, 5.0, 5.0, 5.0, 6.0, 6.0, 6.0 ]
+```
+
+The function has the following additional parameters:
+
+-   **sa1**: stride of the first dimension of `A`.
+-   **sa2**: stride of the second dimension of `A`.
+-   **oa**: starting index for `A`.
+-   **sb1**: stride of the first dimension of `B`.
+-   **sb2**: stride of the second dimension of `B`.
+-   **ob**: starting index for `B`.
+-   **sc1**: stride of the first dimension of `C`.
+-   **sc2**: stride of the second dimension of `C`.
+-   **oc**: starting index for `C`.
+
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example,
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+var A = new Float64Array( [ 0.0, 1.0, 1.0, 1.0, 1.0, 2.0, 1.0, 1.0, 1.0, 3.0 ] );
+var B = new Float64Array( [ 0.0, 0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );
+var C = new Float64Array( [ 0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );
+
+dsymm( 'left', 'lower', 3, 3, 1.0, A, 3, 1, 1, B, 3, 1, 2, 1.0, C, 3, 1, 3 );
+// C => <Float64Array>[ 0.0, 0.0, 0.0, 4.0, 4.0, 4.0, 5.0, 5.0, 5.0, 6.0, 6.0, 6.0 ]
+```
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   `dsymm()` corresponds to the [BLAS][blas] level 3 function [`dsymm`][blas-dsymm].
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var dsymm = require( '@stdlib/blas/base/dsymm' );
+
+var opts = {
+    'dtype': 'float64'
+};
+
+var M = 3;
+var N = 3;
+
+var A = discreteUniform( M*N, 0, 10, opts );
+var B = discreteUniform( M*N, 0, 10, opts );
+var C = discreteUniform( M*N, 0, 10, opts );
+
+dsymm( 'row-major', 'left', 'lower', M, N, 1.0, A, M, B, N, 1.0, C, N );
+console.log( C );
+
+dsymm.ndarray( 'left', 'lower', M, N, 1.0, A, M, 1, 0, B, N, 1, 0, 1.0, C, N, 1, 0 );
+console.log( C );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- C interface documentation. -->
+
+* * *
+
+<section class="c">
+
+## C APIs
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/blas/base/dsymm.h"
+```
+
+#### TODO
+
+TODO.
+
+```c
+TODO
+```
+
+TODO
+
+```c
+TODO
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+TODO
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+[blas]: http://www.netlib.org/blas
+
+[blas-dsymm]: https://www.netlib.org/lapack/explore-html-3.6.1/d1/d54/group__double__blas__level3_ga253c8edb8b21d1b5b1783725c2a6b692.html
+
+[mdn-float64array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Float64Array
+
+[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray
+
+</section>
+
+<!-- /.links -->
diff --git a/lib/node_modules/@stdlib/blas/base/dsymm/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/dsymm/benchmark/benchmark.js
@@ -0,0 +1,105 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2024 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 bench = require( '@stdlib/bench' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var floor = require( '@stdlib/math/base/special/floor' );
+var pkg = require( './../package.json' ).name;
+var dsymm = require( './../lib/dsymm.js' );
+
+
+// VARIABLES //
+
+var options = {
+	'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} N - array dimension size
+* @returns {Function} benchmark function
+*/
+function createBenchmark( N ) {
+	var A = uniform( N*N, -10.0, 10.0, options );
+	var B = uniform( N*N, -10.0, 10.0, options );
+	var C = uniform( N*N, -10.0, 10.0, options );
+	return benchmark;
+
+	/**
+	* Benchmark function.
+	*
+	* @private
+	* @param {Benchmark} b - benchmark instance
+	*/
+	function benchmark( b ) {
+		var z;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			z = dsymm( 'row-major', 'left', 'lower', N, N, 1.0, A, N, B, N, 1.0, C, N );
+			if ( isnan( z[ i%z.length ] ) ) {
+				b.fail( 'should not return NaN' );
+			}
+		}
+		b.toc();
+		if ( isnan( z[ i%z.length ] ) ) {
+			b.fail( 'should not return NaN' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var len;
+	var min;
+	var max;
+	var f;
+	var i;
+
+	min = 1; // 10^min
+	max = 5; // 10^max
+
+	for ( i = min; i <= max; i++ ) {
+		len = floor( pow( pow( 10, i ), 1.0/2.0 ) );
+		f = createBenchmark( len );
+		bench( pkg+':order(A)=row-major,order(B)=row-major,order(C)=row-major,trans(A)=false,trans(B)=false,size='+(len*len), f );
+	}
+}
+
+main();