Skip to content

feat: add blas/base/dsbmv #6650

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
wants to merge 11 commits into
base: develop
Choose a base branch
from
Open
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
266 changes: 266 additions & 0 deletions lib/node_modules/@stdlib/blas/base/dsbmv/README.md
Original file line number Diff line number Diff line change
@@ -0,0 +1,266 @@
<!--

@license Apache-2.0

Copyright (c) 2025 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.

-->

# dsbmv

> Perform the matrix-vector operation `y = alpha*A*x + beta*y` where `alpha` and `beta` are scalars, `x` and `y` are `N` element vectors, and `A` is an `N` by `N` symmetric band matrix, with `K` super-diagonals.

<section class="usage">

## Usage

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

#### dsbmv( order, uplo, N, K, α, A, x, LDA, sx, β, y, sy )

Performs the matrix-vector operation `y = alpha*A*x + beta*y` where `alpha` and `beta` are scalars, `x` and `y` are `N` element vectors, and `A` is an `N` by `N` symmetric band matrix, with `K` super-diagonals.

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

var A = new Float64Array( [ 1.0, 2.0, 4.0, 3.0, 5.0, 0.0 ] );
var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );
var y = new Float64Array( [ 0.0, 0.0, 0.0 ] );

dsbmv( 'row-major', 'lower', 3, 1, 1.0, A, 2, x, 1, 0.0, y, 1 );
// y => <Float64Array>[ 10.0, 25.0, 10.0 ]
```

The function has the following parameters:

- **order**: storage layout.
- **uplo**: specifies whether the upper or lower triangular part of the symmetric matrix `A` is supplied.
- **N**: specifies the order of the matrix `A`.
- **K**: specifies the number of super-diagonals of the matrix `A`
- **α**: scalar constant.
- **A**: packed banded form of a symmetric matrix `A` stored in linear memory as a [`Float64Array`][mdn-float64array].
- **LDA**: stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`)
- **x**: input [`Float64Array`][mdn-float64array].
- **sx**: index increment for `x`.
- **β**: scalar constant.
- **y**: output [`Float64Array`][mdn-float64array].
- **sy**: index increment for `y`.

The stride parameters determine how elements in the input arrays are accessed at runtime. For example, to iterate over the elements of `y` in reverse order,

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

var A = new Float64Array( [ 1.0, 2.0, 4.0, 3.0, 5.0, 0.0 ] );
var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );
var y = new Float64Array( [ 0.0, 0.0, 0.0 ] );

dsbmv( 'row-major', 'lower', 3, 1, 1.0, A, 2, x, 1, 0.0, y, -1 );
// y => <Float64Array>[ 10.0, 25.0, 10.0 ]
```

Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views.

<!-- eslint-disable stdlib/capitalized-comments -->

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

// Initial arrays...
var x0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );
var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );
var A = new Float64Array( [ 1.0, 2.0, 4.0, 3.0, 5.0, 0.0 ] );

// Create offset views...
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); // start at 2nd element

dsbmv( 'row-major', 'lower', 3, 1, 1.0, A, 2, x1, 1, 0.0, y1, 1 );
// y0 => <Float64Array>[ 0.0, 10.0, 25.0, 10.0 ]
```

#### dsbmv.ndarray( uplo, N, K, α, A, sa1, sa2, oa, x, sx, ox, β, y, sy, oy )

Performs the matrix-vector operation `y = alpha*A*x + beta*y` using alternative indexing semantics where `alpha` and `beta` are scalars, `x` and `y` are `N` element vectors, and `A` is an `N` by `N` symmetric band matrix, with `K` super-diagonals.

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

var A = new Float64Array( [ 1.0, 2.0, 4.0, 3.0, 5.0, 0.0 ] );
var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );
var y = new Float64Array( [ 0.0, 0.0, 0.0 ] );

dsbmv.ndarray( 'lower', 3, 1, 1.0, A, 2, 1, 0, x, 1, 0, 0.0, y, 1, 0 );
// y => <Float64Array>[ 10.0, 25.0, 10.0 ]
```

The function has the following additional parameters:

- **oa**: starting index for `A`.
- **sa1**: first dimension index increment for `A`.
- **sa2**: second dimension index increment for `A`.
- **ox**: starting index for `x`.
- **oy**: starting index for `y`.

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( [ 1.0, 2.0, 4.0, 3.0, 5.0, 0.0 ] );
var x = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );
var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );

dsbmv.ndarray( 'lower', 3, 1, 1.0, A, 2, 1, 0, x, 1, 1, 0.0, y, 1, 1 );
// y => <Float64Array>[ 0.0, 10.0, 25.0, 10.0 ]
```

</section>

<!-- /.usage -->

<section class="notes">

## Notes

- `dsbmv()` corresponds to the [BLAS][blas] level 2 function [`dsbmv`][dsbmv].

</section>

<!-- /.notes -->

<section class="examples">

## Examples

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

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

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

var N = 3;
var A = [ 1, 2, 0, 3, 4, 5 ];

var x = discreteUniform( N, -10, 10, opts );
var y = discreteUniform( N, -10, 10, opts );

dsbmv.ndarray( 'upper', N, 1, 1.0, A, 1, 2, 0, x, 1, 0, 1.0, y, 1, 0 );
console.log( y );
```

</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
TODO
```

#### 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

[dsbmv]: https://www.netlib.org/lapack/explore-html-3.6.1/d7/d15/group__double__blas__level2_ga5c7ca036c788c5fd42e04ade0dc92d44.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 -->
105 changes: 105 additions & 0 deletions lib/node_modules/@stdlib/blas/base/dsbmv/benchmark/benchmark.js
Original file line number Diff line number Diff line change
@@ -0,0 +1,105 @@
/**
* @license Apache-2.0
*
* Copyright (c) 2025 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 dsbmv = require( './../lib/dsbmv.js' );


// VARIABLES //

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


// FUNCTIONS //

/**
* Creates a benchmark function.
*
* @private
* @param {PositiveInteger} len - array length
* @returns {Function} benchmark function
*/
function createBenchmark( len ) {
var x = uniform( len, -10.0, 10.0, options );
var y = uniform( len, -10.0, 10.0, options );
var A = [ 0,
9,
10,
11,
12,
5,
1,
2,
0 ];
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 = dsbmv( 'row-major', 'upper', len, 1.0, 1, A, 2, x, 1, 1.0, y, 1 );
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 f;

len = floor( pow( pow( 10, 1 ), 1.0/2.0 ) );
f = createBenchmark( len );
bench( pkg+':size='+(len*len), f );
}

main();
Loading