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feat: add blas/base/sgemm #2742

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8ad06b6
feat: add BLAS Level 3 routine for sgemm
aman-095 Aug 5, 2024
ce70f16
docs: update description
kgryte Aug 7, 2024
07e4a0e
temp: refactor implementation
kgryte Aug 9, 2024
bd3faff
refactor: replace loop with BLAS sdot
kgryte Aug 9, 2024
0b644bf
refactor: add loop tiling algorithm
kgryte Aug 9, 2024
6a8041f
fix: update transpose literal
kgryte Aug 9, 2024
bab523b
docs: update example
kgryte Aug 9, 2024
fa068e6
Merge branch 'develop' of https://github.com/stdlib-js/stdlib into pr…
kgryte Aug 9, 2024
50ff368
bench: add benchmark for native and ndarray implementation
aman-095 Aug 10, 2024
0c9204b
fix: address buffer overflow bug
kgryte Aug 10, 2024
1c53ffc
Merge branch 'sgemm' of https://github.com/aman-095/stdlib into pr/am…
kgryte Aug 10, 2024
4318626
chore: update copyright years
stdlib-bot Aug 10, 2024
e67b0b4
Merge branch 'stdlib-js:develop' into sgemm
aman-095 Aug 10, 2024
470d540
docs: add types and repl
aman-095 Aug 10, 2024
23986e6
test: add test cases for native and ndarray implementation
aman-095 Aug 13, 2024
44afbdc
bench: reduce max power to 5
aman-095 Aug 13, 2024
ab05c1a
docs: add README, test.js and update examples
aman-095 Aug 13, 2024
fbdabab
bench: add missing facets and reduce max power
kgryte Aug 13, 2024
9d5236b
docs: fix wrapping and visually group related arguments
kgryte Aug 13, 2024
9d02719
docs: add todos
kgryte Aug 13, 2024
c57d21a
docs: fix descriptions
kgryte Aug 13, 2024
0dbc0be
docs: fix examples and style
kgryte Aug 14, 2024
09e0cb9
test: simplify test descriptions
kgryte Aug 15, 2024
a84ddd3
test: simplify test descriptions
kgryte Aug 15, 2024
e47811c
test: simplify test descriptions
kgryte Aug 15, 2024
5b77a41
refactor: reduce code duplication and update descriptions
kgryte Aug 15, 2024
f79d1b1
test: add missing tests
kgryte Aug 15, 2024
d185ae7
test: add missing tests
kgryte Aug 15, 2024
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test: add tests to verify blocked iteration behavior
kgryte Aug 15, 2024
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259 changes: 259 additions & 0 deletions lib/node_modules/@stdlib/blas/base/sgemm/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.

-->

# sgemm

> 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 sgemm = require( '@stdlib/blas/base/sgemm' );
```

#### sgemm( 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(A)` 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 Float32Array = require( '@stdlib/array/float32' );

var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );
var B = new Float32Array( [ 1.0, 1.0, 0.0, 1.0 ] );
var C = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );

sgemm( 'row-major', 'no-transpose', 'no-transpose', 2, 2, 2, 1.0, A, 2, B, 2, 1.0, C, 2 );
// C => <Float32Array>[ 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 [`Float32Array`][mdn-float32array].
- **lda**: stride of the first dimension of `A` (leading dimension of `A`).
- **B**: second input matrix stored in linear memory as a [`Float32Array`][mdn-float32array].
- **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 [`Float32Array`][mdn-float32array].
- **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 Float32Array = require( '@stdlib/array/float32' );

var A = new Float32Array( [ 1.0, 2.0, 0.0, 0.0, 3.0, 4.0, 0.0, 0.0 ] );
var B = new Float32Array( [ 1.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0 ] );
var C = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );

sgemm( 'row-major', 'no-transpose', 'no-transpose', 2, 2, 2, 1.0, A, 4, B, 4, 1.0, C, 2 );
// C => <Float32Array>[ 2.0, 5.0, 6.0, 11.0 ]
```

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

#### sgemm.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(A)` 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 Float32Array = require( '@stdlib/array/float32' );

var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );
var B = new Float32Array( [ 1.0, 1.0, 0.0, 1.0 ] );
var C = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );

sgemm.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 => <Float32Array>[ 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 Float32Array = require( '@stdlib/array/float32' );

var A = new Float32Array( [ 0.0, 0.0, 1.0, 3.0, 2.0, 4.0 ] );
var B = new Float32Array( [ 0.0, 1.0, 0.0, 1.0, 1.0 ] );
var C = new Float32Array( [ 0.0, 0.0, 0.0, 1.0, 3.0, 2.0, 4.0 ] );

sgemm.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 => <Float32Array>[ 0.0, 0.0, 0.0, 2.0, 6.0, 5.0, 11.0 ]
```

</section>

<!-- /.usage -->

<section class="notes">

## Notes

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

</section>

<!-- /.notes -->

<section class="examples">

## Examples

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

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

var opts = {
'dtype': 'float32'
};

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

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

sgemm.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/sgemm.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-sgemm]: https://www.netlib.org/lapack/explore-html/dd/d09/group__gemm_ga8cad871c590600454d22564eff4fed6b.html#ga8cad871c590600454d22564eff4fed6b

[mdn-float32array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Float32Array

[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 isnanf = require( '@stdlib/math/base/assert/is-nanf' );
var pow = require( '@stdlib/math/base/special/pow' );
var floor = require( '@stdlib/math/base/special/floor' );
var pkg = require( './../package.json' ).name;
var sgemm = require( './../lib/ndarray.js' );


// VARIABLES //

var options = {
'dtype': 'float32'
};


// 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 = sgemm( 'no-transpose', 'no-transpose', N, N, N, 1.0, A, 1, N, 0, B, 1, N, 0, 1.0, C, 1, N, 0 );
if ( isnanf( z[ i%z.length ] ) ) {
b.fail( 'should not return NaN' );
}
}
b.toc();
if ( isnanf( 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 = 4; // 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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