@stdlib/blas-ext-base-wasm
v0.1.1
Published
Extensions to basic linear algebra subprograms (BLAS) compiled to WebAssembly.
Readme
Extended BLAS
Extensions to basic linear algebra subprograms (BLAS) compiled to WebAssembly.
Installation
npm install @stdlib/blas-ext-base-wasmUsage
var ns = require( '@stdlib/blas-ext-base-wasm' );ns
Namespace for extensions to basic linear algebra subprograms (BLAS) compiled to WebAssembly.
var o = ns;
// returns {...}dapx( N, alpha, x, strideX ): add a scalar constant to each element in a double-precision floating-point strided array.dapxsum( N, alpha, x, strideX ): add a scalar constant to each double-precision floating-point strided array element and compute the sum.dapxsumkbn( N, alpha, x, strideX ): add a scalar constant to each double-precision floating-point strided array element and compute the sum using an improved Kahan–Babuška algorithm.dapxsumors( N, alpha, x, strideX ): add a scalar constant to each double-precision floating-point strided array element and compute the sum using ordinary recursive summation.dapxsumpw( N, alpha, x, strideX ): add a scalar constant to each double-precision floating-point strided array element and compute the sum using pairwise summation.dasumpw( N, x, strideX ): calculate the sum of absolute values (L1 norm) of double-precision floating-point strided array elements using pairwise summation.dnanasumors( N, x, strideX ): calculate the sum of absolute values (L1 norm) of double-precision floating-point strided array elements, ignoringNaNvalues and using ordinary recursive summation.dnansumkbn2( N, x, strideX ): calculate the sum of double-precision floating-point strided array elements, ignoringNaNvalues and using a second-order iterative Kahan–Babuška algorithm.dnansumpw( N, x, strideX ): calculate the sum of double-precision floating-point strided array elements, ignoringNaNvalues and using pairwise summation.sapxsumkbn( N, alpha, x, strideX ): add a scalar constant to each single-precision floating-point strided array element and compute the sum using an improved Kahan–Babuška algorithm.
Examples
var objectKeys = require( '@stdlib/utils-keys' );
var ns = require( '@stdlib/blas-ext-base-wasm' );
console.log( objectKeys( ns ) );Notice
This package is part of 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, see the main project repository.
Community
License
See LICENSE.
Copyright
Copyright © 2016-2026. The Stdlib Authors.
