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blas-base-wasm-dsdot

Compute the dot product of `x` and `y` with extended accumulation and result.

https://github.com/stdlib-js/blas-base-wasm-dsdot

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algebra array blas dot dsdot float32 float32array javascript level-1 linear math mathematics ndarray node node-js nodejs single stdlib subroutines vector
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Compute the dot product of `x` and `y` with extended accumulation and result.

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algebra array blas dot dsdot float32 float32array javascript level-1 linear math mathematics ndarray node node-js nodejs single stdlib subroutines vector
Created 10 months ago · Last pushed 7 months ago
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README.md

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dsdot

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Compute the dot product of x and y with extended accumulation and result.

## Installation ```bash npm install @stdlib/blas-base-wasm-dsdot ``` Alternatively, - To load the package in a website via a `script` tag without installation and bundlers, use the [ES Module][es-module] available on the [`esm`][esm-url] branch (see [README][esm-readme]). - If you are using Deno, visit the [`deno`][deno-url] branch (see [README][deno-readme] for usage intructions). - For use in Observable, or in browser/node environments, use the [Universal Module Definition (UMD)][umd] build available on the [`umd`][umd-url] branch (see [README][umd-readme]). The [branches.md][branches-url] file summarizes the available branches and displays a diagram illustrating their relationships. To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.
## Usage ```javascript var dsdot = require( '@stdlib/blas-base-wasm-dsdot' ); ``` #### dsdot.main( N, x, strideX, y, strideY ) Computes the dot product of `x` and `y` with extended accumulation and result. ```javascript var Float32Array = require( '@stdlib/array-float32' ); var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ); var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ); var z = dsdot.main( x.length, x, 1, y, 1 ); // returns -5.0 ``` The function has the following parameters: - **N**: number of indexed elements. - **x**: first input [`Float32Array`][@stdlib/array/float32]. - **strideX**: index increment for `x`. - **y**: second input [`Float32Array`][@stdlib/array/float32]. - **strideY**: index increment for `y`. The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to calculate the dot product of every other value in `x` and the first `N` elements of `y` in reverse order, ```javascript var Float32Array = require( '@stdlib/array-float32' ); var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] ); var z = dsdot.main( 3, x, 2, y, -1 ); // returns 9.0 ``` Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. ```javascript var Float32Array = require( '@stdlib/array-float32' ); // Initial arrays... var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); // Create offset views... var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element var z = dsdot.main( 3, x1, -2, y1, 1 ); // returns 128.0 ``` #### dsdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) Computes the dot product of `x` and `y` with extended accumulation and result using alternative indexing semantics. ```javascript var Float32Array = require( '@stdlib/array-float32' ); var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ); var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ); var z = dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 ); // returns -5.0 ``` The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetY**: 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, to calculate the dot product of every other value in `x` starting from the second value with the last 3 elements in `y` in reverse order ```javascript var Float32Array = require( '@stdlib/array-float32' ); var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); var y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); var z = dsdot.ndarray( 3, x, 2, 1, y, -1, y.length-1 ); // returns 128.0 ``` * * * ### Module #### dsdot.Module( memory ) Returns a new WebAssembly [module wrapper][@stdlib/wasm/module-wrapper] instance which uses the provided WebAssembly [memory][@stdlib/wasm/memory] instance as its underlying memory. ```javascript var Memory = require( '@stdlib/wasm-memory' ); // Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB): var mem = new Memory({ 'initial': 10, 'maximum': 100 }); // Create a BLAS routine: var mod = new dsdot.Module( mem ); // returns // Initialize the routine: mod.initializeSync(); ``` #### dsdot.Module.prototype.main( N, xp, sx, yp, sy ) Computes the dot product of `x` and `y` with extended accumulation and result. ```javascript var Memory = require( '@stdlib/wasm-memory' ); var oneTo = require( '@stdlib/array-one-to' ); var ones = require( '@stdlib/array-ones' ); var zeros = require( '@stdlib/array-zeros' ); var bytesPerElement = require( '@stdlib/ndarray-base-bytes-per-element' ); // Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB): var mem = new Memory({ 'initial': 10, 'maximum': 100 }); // Create a BLAS routine: var mod = new dsdot.Module( mem ); // returns // Initialize the routine: mod.initializeSync(); // Define a vector data type: var dtype = 'float32'; // Specify a vector length: var N = 5; // Define pointers (i.e., byte offsets) for storing two vectors: var xptr = 0; var yptr = N * bytesPerElement( dtype ); // Write vector values to module memory: mod.write( xptr, oneTo( N, dtype ) ); mod.write( yptr, ones( N, dtype ) ); // Perform computation: var z = mod.main( N, xptr, 1, yptr, 1 ); console.log( z ); ``` The function has the following parameters: - **N**: number of indexed elements. - **xp**: first input [`Float32Array`][@stdlib/array/float32] pointer (i.e., byte offset). - **sx**: index increment for `x`. - **yp**: second input [`Float32Array`][@stdlib/array/float32] pointer (i.e., byte offset). - **sy**: index increment for `y`. #### dsdot.Module.prototype.ndarray( N, xp, sx, ox, yp, sy, oy ) Computes the dot product of `x` and `y` with extended accumulation and result using alternative indexing semantics. ```javascript var Memory = require( '@stdlib/wasm-memory' ); var oneTo = require( '@stdlib/array-one-to' ); var ones = require( '@stdlib/array-ones' ); var zeros = require( '@stdlib/array-zeros' ); var bytesPerElement = require( '@stdlib/ndarray-base-bytes-per-element' ); // Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB): var mem = new Memory({ 'initial': 10, 'maximum': 100 }); // Create a BLAS routine: var mod = new dsdot.Module( mem ); // returns // Initialize the routine: mod.initializeSync(); // Define a vector data type: var dtype = 'float32'; // Specify a vector length: var N = 5; // Define pointers (i.e., byte offsets) for storing two vectors: var xptr = 0; var yptr = N * bytesPerElement( dtype ); // Write vector values to module memory: mod.write( xptr, oneTo( N, dtype ) ); mod.write( yptr, ones( N, dtype ) ); // Perform computation: var z = mod.ndarray( N, xptr, 1, 0, yptr, 1, 0 ); console.log( z ); ``` The function has the following additional parameters: - **ox**: starting index for `x`. - **oy**: starting index for `y`.
* * * ## Notes - If `N <= 0`, both `main` and `ndarray` methods return `0.0`. - This package implements routines using WebAssembly. When provided arrays which are not allocated on a `dsdot` module memory instance, data must be explicitly copied to module memory prior to computation. Data movement may entail a performance cost, and, thus, if you are using arrays external to module memory, you should prefer using [`@stdlib/blas-base/dsdot`][@stdlib/blas/base/dsdot]. However, if working with arrays which are allocated and explicitly managed on module memory, you can achieve better performance when compared to the pure JavaScript implementations found in [`@stdlib/blas/base/dsdot`][@stdlib/blas/base/dsdot]. Beware that such performance gains may come at the cost of additional complexity when having to perform manual memory management. Choosing between implementations depends heavily on the particular needs and constraints of your application, with no one choice universally better than the other. - `dsdot()` corresponds to the [BLAS][blas] level 1 function [`dsdot`][dsdot].
* * * ## Examples ```javascript var discreteUniform = require( '@stdlib/random-array-discrete-uniform' ); var dsdot = require( '@stdlib/blas-base-wasm-dsdot' ); var opts = { 'dtype': 'float32' }; var x = discreteUniform( 10, 0, 100, opts ); console.log( x ); var y = discreteUniform( x.length, 0, 10, opts ); console.log( y ); var z = dsdot.ndarray( x.length, x, 1, 0, y, -1, y.length-1 ); console.log( z ); ```
* * * ## Notice This package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. For more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib]. #### Community [![Chat][chat-image]][chat-url] --- ## License See [LICENSE][stdlib-license]. ## Copyright Copyright © 2016-2025. The Stdlib [Authors][stdlib-authors].

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Standard library for JavaScript.

Citation (CITATION.cff) 

cff-version: 1.2.0
title: stdlib
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  If you use this software, please cite it using the
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authors:
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    url: https://github.com/stdlib-js/stdlib/graphs/contributors

repository-code: https://github.com/stdlib-js/stdlib
url: https://stdlib.io

abstract: |
  Standard library for JavaScript and Node.js.

keywords:
  - JavaScript
  - Node.js
  - TypeScript
  - standard library
  - scientific computing
  - numerical computing
  - statistical computing

license: Apache-2.0 AND BSL-1.0

date-released: 2016

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