time-to-botec

Benchmark sampling in different programming languages
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ndarray.js (2114B)

      1 /**
      2 * @license Apache-2.0
      3 *
      4 * Copyright (c) 2020 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 = 6;
     24 
     25 
     26 // MAIN //
     27 
     28 /**
     29 * Computes the sum of single-precision floating-point strided array elements using ordinary recursive summation with extended accumulation and returning an extended precision result.
     30 *
     31 * @param {PositiveInteger} N - number of indexed elements
     32 * @param {Float32Array} x - input array
     33 * @param {integer} stride - stride length
     34 * @param {NonNegativeInteger} offset - starting index
     35 * @returns {number} sum
     36 *
     37 * @example
     38 * var Float32Array = require( '@stdlib/array/float32' );
     39 * var floor = require( '@stdlib/math/base/special/floor' );
     40 *
     41 * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
     42 * var N = floor( x.length / 2 );
     43 *
     44 * var v = dssumors( N, x, 2, 1 );
     45 * // returns 5.0
     46 */
     47 function dssumors( N, x, stride, offset ) {
     48 	var sum;
     49 	var ix;
     50 	var m;
     51 	var i;
     52 
     53 	sum = 0.0;
     54 	if ( N <= 0 ) {
     55 		return sum;
     56 	}
     57 	if ( N === 1 || stride === 0 ) {
     58 		return x[ offset ];
     59 	}
     60 	ix = offset;
     61 
     62 	// If the stride is equal to `1`, use unrolled loops...
     63 	if ( stride === 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 				sum += x[ ix ];
     70 				ix += stride;
     71 			}
     72 		}
     73 		if ( N < M ) {
     74 			return sum;
     75 		}
     76 		for ( i = m; i < N; i += M ) {
     77 			sum += x[ix] + x[ix+1] + x[ix+2] + x[ix+3] + x[ix+4] + x[ix+5];
     78 			ix += M;
     79 		}
     80 		return sum;
     81 	}
     82 	for ( i = 0; i < N; i++ ) {
     83 		sum += x[ ix ];
     84 		ix += stride;
     85 	}
     86 	return sum;
     87 }
     88 
     89 
     90 // EXPORTS //
     91 
     92 module.exports = dssumors;