ndarray.js (2350B)
1 /** 2 * @license Apache-2.0 3 * 4 * Copyright (c) 2018 The Stdlib Authors. 5 * 6 * Licensed under the Apache License, Version 2.0 (the "License"); 7 * you may not use this file except in compliance with the License. 8 * You may obtain a copy of the License at 9 * 10 * http://www.apache.org/licenses/LICENSE-2.0 11 * 12 * Unless required by applicable law or agreed to in writing, software 13 * distributed under the License is distributed on an "AS IS" BASIS, 14 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 15 * See the License for the specific language governing permissions and 16 * limitations under the License. 17 */ 18 19 'use strict'; 20 21 // VARIABLES // 22 23 var M = 4; 24 25 26 // MAIN // 27 28 /** 29 * Multiplies a vector `x` by a constant and adds the result to `y`. 30 * 31 * @param {PositiveInteger} N - number of elements 32 * @param {number} alpha - scalar 33 * @param {Float64Array} x - input array 34 * @param {integer} strideX - `x` stride length 35 * @param {NonNegativeInteger} offsetX - starting `x` index 36 * @param {Float64Array} y - destination array 37 * @param {integer} strideY - `y` stride length 38 * @param {NonNegativeInteger} offsetY - starting `y` index 39 * @returns {Float64Array} `y` 40 * 41 * @example 42 * var Float64Array = require( '@stdlib/array/float64' ); 43 * 44 * var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); 45 * var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] ); 46 * var alpha = 5.0; 47 * 48 * daxpy( x.length, alpha, x, 1, 0, y, 1, 0 ); 49 * // y => <Float64Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ] 50 */ 51 function daxpy( N, alpha, x, strideX, offsetX, y, strideY, offsetY ) { 52 var ix; 53 var iy; 54 var m; 55 var i; 56 if ( N <= 0 || alpha === 0.0 ) { 57 return y; 58 } 59 ix = offsetX; 60 iy = offsetY; 61 62 // Use unrolled loops if both strides are equal to `1`... 63 if ( strideX === 1 && strideY === 1 ) { 64 m = N % M; 65 66 // If we have a remainder, run a clean-up loop... 67 if ( m > 0 ) { 68 for ( i = 0; i < m; i++ ) { 69 y[ iy ] += alpha * x[ ix ]; 70 ix += strideX; 71 iy += strideY; 72 } 73 } 74 if ( N < M ) { 75 return y; 76 } 77 for ( i = m; i < N; i += M ) { 78 y[ iy ] += alpha * x[ ix ]; 79 y[ iy+1 ] += alpha * x[ ix+1 ]; 80 y[ iy+2 ] += alpha * x[ ix+2 ]; 81 y[ iy+3 ] += alpha * x[ ix+3 ]; 82 ix += M; 83 iy += M; 84 } 85 return y; 86 } 87 for ( i = 0; i < N; i++ ) { 88 y[ iy ] += alpha * x[ ix ]; 89 ix += strideX; 90 iy += strideY; 91 } 92 return y; 93 } 94 95 96 // EXPORTS // 97 98 module.exports = daxpy;