daxpy.js (2243B)
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 {Float64Array} y - destination array 36 * @param {integer} strideY - `y` stride length 37 * @returns {Float64Array} `y` 38 * 39 * @example 40 * var Float64Array = require( '@stdlib/array/float64' ); 41 * 42 * var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); 43 * var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] ); 44 * var alpha = 5.0; 45 * 46 * daxpy( x.length, alpha, x, 1, y, 1 ); 47 * // y => <Float64Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ] 48 */ 49 function daxpy( N, alpha, x, strideX, y, strideY ) { 50 var ix; 51 var iy; 52 var m; 53 var i; 54 if ( N <= 0 || alpha === 0.0 ) { 55 return y; 56 } 57 // Use unrolled loops if both strides are equal to `1`... 58 if ( strideX === 1 && strideY === 1 ) { 59 m = N % M; 60 61 // If we have a remainder, run a clean-up loop... 62 if ( m > 0 ) { 63 for ( i = 0; i < m; i++ ) { 64 y[ i ] += alpha * x[ i ]; 65 } 66 } 67 if ( N < M ) { 68 return y; 69 } 70 for ( i = m; i < N; i += M ) { 71 y[ i ] += alpha * x[ i ]; 72 y[ i+1 ] += alpha * x[ i+1 ]; 73 y[ i+2 ] += alpha * x[ i+2 ]; 74 y[ i+3 ] += alpha * x[ i+3 ]; 75 } 76 return y; 77 } 78 if ( strideX < 0 ) { 79 ix = (1-N) * strideX; 80 } else { 81 ix = 0; 82 } 83 if ( strideY < 0 ) { 84 iy = (1-N) * strideY; 85 } else { 86 iy = 0; 87 } 88 for ( i = 0; i < N; i++ ) { 89 y[ iy ] += alpha * x[ ix ]; 90 ix += strideX; 91 iy += strideY; 92 } 93 return y; 94 } 95 96 97 // EXPORTS // 98 99 module.exports = daxpy;