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feat: add blas/base/dgemm #2541

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9c038db
chore: init blas/base/dgemm
Pranavchiku Jul 9, 2024
6c1270a
fix: suppress max-len error in ndarray.js
Pranavchiku Jul 9, 2024
58859fd
chore: import dgemm from lib instead of base.js in example
Pranavchiku Jul 9, 2024
638a126
chore: update examples/index.js to use generic values
Pranavchiku Jul 10, 2024
a14bb5d
chore: test if what is pushed
Pranavchiku Jul 10, 2024
6b03e76
Merge remote-tracking branch 'origin/develop' into dgemm
aman-095 Aug 13, 2024
37081e6
refactor: update implementation, add docs, tests, benchmark and README
aman-095 Aug 13, 2024
f909cc2
bench: add missing facets
aman-095 Aug 15, 2024
c0840c3
docs: fix wrapping and visually group related arguments, add todos, f…
aman-095 Aug 15, 2024
fd15263
test: simplify test descriptions and add missing tests
aman-095 Aug 15, 2024
9fd11b9
refactor: reduce code duplication and update descriptions
aman-095 Aug 15, 2024
ae20b36
Merge branch 'develop' into dgemm
Pranavchiku Aug 15, 2024
81a518d
bench: fix facets
kgryte Aug 15, 2024
eb9573f
bench: fix facets
kgryte Aug 15, 2024
15b8e37
docs: fix descriptions
kgryte Aug 15, 2024
f81ea5a
docs: fix descriptions
kgryte Aug 15, 2024
0e356e2
docs: fix descriptions
kgryte Aug 15, 2024
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docs: fix descriptions
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docs: fix descriptions
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style: remove blank lines
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docs: fix descriptions
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259 changes: 259 additions & 0 deletions lib/node_modules/@stdlib/blas/base/dgemm/README.md
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<!--

@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.

-->

# dgemm

> Perform the matrix-matrix operation `C = α*op(A)*op(B) + β*C` where `op(X)` is one of the `op(X) = X`, or `op(X) = X^T`.

<section class = "usage">

## Usage

```javascript
var dgemm = require( '@stdlib/blas/base/dgemm' );
```

#### dgemm( ord, ta, tb, M, N, K, α, A, lda, B, ldb, β, C, ldc )

Performs the matrix-matrix operation `C = α*op(A)*op(B) + β*C` where `op(X)` is either `op(X) = X` or `op(X) = X^T`, `α` and `β` are scalars, `A`, `B`, and `C` are matrices, with `op(A)` an `M` by `K` matrix, `op(B)` a `K` by `N` matrix, and `C` an `M` by `N` matrix.

```javascript
var Float64Array = require( '@stdlib/array/float64' );

var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
var B = new Float64Array( [ 1.0, 1.0, 0.0, 1.0 ] );
var C = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );

dgemm( 'row-major', 'no-transpose', 'no-transpose', 2, 2, 2, 1.0, A, 2, B, 2, 1.0, C, 2 );
// C => <Float64Array>[ 2.0, 5.0, 6.0, 11.0 ]
```

The function has the following parameters:

- **ord**: storage layout.
- **ta**: specifies whether `A` should be transposed, conjugate-transposed, or not transposed.
- **tb**: specifies whether `B` should be transposed, conjugate-transposed, or not transposed.
- **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`.
- **K**: number of columns in the matrix `op(A)` and number of rows in the matrix `op(B)`.
- **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 constant
- **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

```javascript
var Float64Array = require( '@stdlib/array/float64' );

var A = new Float64Array( [ 1.0, 2.0, 0.0, 0.0, 3.0, 4.0, 0.0, 0.0 ] );
var B = new Float64Array( [ 1.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0 ] );
var C = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );

dgemm( 'row-major', 'no-transpose', 'no-transpose', 2, 2, 2, 1.0, A, 4, B, 4, 1.0, C, 2 );
// C => <Float64Array>[ 2.0, 5.0, 6.0, 11.0 ]
```

<!-- lint disable maximum-heading-length -->

#### dgemm.ndarray( ta, tb, M, N, K, α, A, sa1, sa2, oa, B, sb1, sb2, ob, β, C, sc1, sc2, oc )

Performs the matrix-matrix operation `C = α*op(A)*op(B) + β*C`, using alternative indexing semantics and where `op(X)` is either `op(X) = X` or `op(X) = X^T`, `α` and `β` are scalars, `A`, `B`, and `C` are matrices, with `op(A)` an `M` by `K` matrix, `op(B)` a `K` by `N` matrix, and `C` an `M` by `N` matrix.

```javascript
var Float64Array = require( '@stdlib/array/float64' );

var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );
var B = new Float64Array( [ 1.0, 1.0, 0.0, 1.0 ] );
var C = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );

dgemm.ndarray( 'no-transpose', 'no-transpose', 2, 2, 2, 1.0, A, 2, 1, 0, B, 2, 1, 0, 1.0, C, 2, 1, 0 );
// C => <Float64Array>[ 2.0, 5.0, 6.0, 11.0 ]
```

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, 0.0, 1.0, 3.0, 2.0, 4.0 ] );
var B = new Float64Array( [ 0.0, 1.0, 0.0, 1.0, 1.0 ] );
var C = new Float64Array( [ 0.0, 0.0, 0.0, 1.0, 3.0, 2.0, 4.0 ] );

dgemm.ndarray( 'no-transpose', 'no-transpose', 2, 2, 2, 1.0, A, 1, 2, 2, B, 1, 2, 1, 1.0, C, 1, 2, 3 );
// C => <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 6.0, 5.0, 11.0 ]
```

</section>

<!-- /.usage -->

<section class="notes">

## Notes

- `dgemm()` corresponds to the [BLAS][blas] level 3 function [`dgemm`][blas-dgemm].

</section>

<!-- /.notes -->

<section class="examples">

## Examples

<!-- eslint no-undef: "error" -->

```javascript
var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
var dgemm = require( '@stdlib/blas/base/dgemm' );

var opts = {
'dtype': 'float64'
};

var M = 3;
var N = 4;
var K = 2;

var A = discreteUniform( M*K, 0, 10, opts ); // 3x2
var B = discreteUniform( K*N, 0, 10, opts ); // 2x4
var C = discreteUniform( M*N, 0, 10, opts ); // 3x4

dgemm( 'row-major', 'no-transpose', 'no-transpose', M, N, K, 1.0, A, K, B, N, 1.0, C, N );
console.log( C );

dgemm.ndarray( 'no-transpose', 'no-transpose', M, N, K, 1.0, A, K, 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/dgemm.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-dgemm]: https://www.netlib.org/lapack/explore-html/dd/d09/group__gemm_ga1e899f8453bcbfde78e91a86a2dab984.html#ga1e899f8453bcbfde78e91a86a2dab984

[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 -->
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/**
* @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 dgemm = require( './../lib/ndarray.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 = dgemm( 'no-transpose', 'no-transpose', N, N, N, 1.0, A, 1, N, 0, B, 1, N, 0, 1.0, C, 1, N, 0 );
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+':ndarray:order(A)=column-major,order(B)=column-major,order(C)=column-major,trans(A)=false,trans(B)=false,size='+(len*len), f );
}
}

main();
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