time-to-botec

Benchmark sampling in different programming languages
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README.md (6364B)


      1 <!--
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      3 @license Apache-2.0
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      5 Copyright (c) 2020 The Stdlib Authors.
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      7 Licensed under the Apache License, Version 2.0 (the "License");
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     11    http://www.apache.org/licenses/LICENSE-2.0
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     13 Unless required by applicable law or agreed to in writing, software
     14 distributed under the License is distributed on an "AS IS" BASIS,
     15 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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     20 
     21 # dcusumpw
     22 
     23 > Calculate the cumulative sum of double-precision floating-point strided array elements using pairwise summation.
     24 
     25 <section class="intro">
     26 
     27 </section>
     28 
     29 <!-- /.intro -->
     30 
     31 <section class="usage">
     32 
     33 ## Usage
     34 
     35 ```javascript
     36 var dcusumpw = require( '@stdlib/blas/ext/base/dcusumpw' );
     37 ```
     38 
     39 #### dcusumpw( N, sum, x, strideX, y, strideY )
     40 
     41 Computes the cumulative sum of double-precision floating-point strided array elements using pairwise summation.
     42 
     43 ```javascript
     44 var Float64Array = require( '@stdlib/array/float64' );
     45 
     46 var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
     47 var y = new Float64Array( x.length );
     48 
     49 dcusumpw( x.length, 0.0, x, 1, y, 1 );
     50 // y => <Float64Array>[ 1.0, -1.0, 1.0 ]
     51 
     52 x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
     53 y = new Float64Array( x.length );
     54 
     55 dcusumpw( x.length, 10.0, x, 1, y, 1 );
     56 // y => <Float64Array>[ 11.0, 9.0, 11.0 ]
     57 ```
     58 
     59 The function has the following parameters:
     60 
     61 -   **N**: number of indexed elements.
     62 -   **sum**: initial sum.
     63 -   **x**: input [`Float64Array`][@stdlib/array/float64].
     64 -   **strideX**: index increment for `x`.
     65 -   **y**: output [`Float64Array`][@stdlib/array/float64].
     66 -   **strideY**: index increment for `y`.
     67 
     68 The `N` and `stride` parameters determine which elements in `x` and `y` are accessed at runtime. For example, to compute the cumulative sum of every other element in `x`,
     69 
     70 ```javascript
     71 var Float64Array = require( '@stdlib/array/float64' );
     72 var floor = require( '@stdlib/math/base/special/floor' );
     73 
     74 var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
     75 var y = new Float64Array( x.length );
     76 
     77 var N = floor( x.length / 2 );
     78 
     79 var v = dcusumpw( N, 0.0, x, 2, y, 1 );
     80 // y => <Float64Array>[ 1.0, 3.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ]
     81 ```
     82 
     83 Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views.
     84 
     85 <!-- eslint-disable stdlib/capitalized-comments -->
     86 
     87 ```javascript
     88 var Float64Array = require( '@stdlib/array/float64' );
     89 var floor = require( '@stdlib/math/base/special/floor' );
     90 
     91 // Initial arrays...
     92 var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
     93 var y0 = new Float64Array( x0.length );
     94 
     95 // Create offset views...
     96 var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
     97 var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element
     98 
     99 var N = floor( x0.length / 2 );
    100 
    101 dcusumpw( N, 0.0, x1, -2, y1, 1 );
    102 // y0 => <Float64Array>[ 0.0, 0.0, 0.0, 4.0, 6.0, 4.0, 5.0, 0.0 ]
    103 ```
    104 
    105 #### dcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )
    106 
    107 Computes the cumulative sum of double-precision floating-point strided array elements using pairwise summation and alternative indexing semantics.
    108 
    109 ```javascript
    110 var Float64Array = require( '@stdlib/array/float64' );
    111 
    112 var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
    113 var y = new Float64Array( x.length );
    114 
    115 dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 );
    116 // y => <Float64Array>[ 1.0, -1.0, 1.0 ]
    117 ```
    118 
    119 The function has the following additional parameters:
    120 
    121 -   **offsetX**: starting index for `x`.
    122 -   **offsetY**: starting index for `y`.
    123 
    124 While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, `offsetX` and `offsetY` parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative sum of every other value in `x` starting from the second value and to store in the last `N` elements of `y` starting from the last element
    125 
    126 ```javascript
    127 var Float64Array = require( '@stdlib/array/float64' );
    128 var floor = require( '@stdlib/math/base/special/floor' );
    129 
    130 var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
    131 var y = new Float64Array( x.length );
    132 
    133 var N = floor( x.length / 2 );
    134 
    135 dcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 );
    136 // y => <Float64Array>[ 0.0, 0.0, 0.0, 0.0, 5.0, 1.0, -1.0, 1.0 ]
    137 ```
    138 
    139 </section>
    140 
    141 <!-- /.usage -->
    142 
    143 <section class="notes">
    144 
    145 ## Notes
    146 
    147 -   If `N <= 0`, both functions return `y` unchanged.
    148 -   In general, pairwise summation is more numerically stable than ordinary recursive summation (i.e., "simple" summation), with slightly worse performance. While not the most numerically stable summation technique (e.g., compensated summation techniques such as the Kahan–Babuška-Neumaier algorithm are generally more numerically stable), pairwise summation strikes a reasonable balance between numerical stability and performance. If either numerical stability or performance is more desirable for your use case, consider alternative summation techniques.
    149 
    150 </section>
    151 
    152 <!-- /.notes -->
    153 
    154 <section class="examples">
    155 
    156 ## Examples
    157 
    158 <!-- eslint no-undef: "error" -->
    159 
    160 ```javascript
    161 var randu = require( '@stdlib/random/base/randu' );
    162 var round = require( '@stdlib/math/base/special/round' );
    163 var Float64Array = require( '@stdlib/array/float64' );
    164 var dcusumpw = require( '@stdlib/blas/ext/base/dcusumpw' );
    165 
    166 var y;
    167 var x;
    168 var i;
    169 
    170 x = new Float64Array( 10 );
    171 y = new Float64Array( x.length );
    172 for ( i = 0; i < x.length; i++ ) {
    173     x[ i ] = round( randu()*100.0 );
    174 }
    175 console.log( x );
    176 console.log( y );
    177 
    178 dcusumpw( x.length, 0.0, x, 1, y, -1 );
    179 console.log( y );
    180 ```
    181 
    182 </section>
    183 
    184 <!-- /.examples -->
    185 
    186 * * *
    187 
    188 <section class="references">
    189 
    190 ## References
    191 
    192 -   Higham, Nicholas J. 1993. "The Accuracy of Floating Point Summation." _SIAM Journal on Scientific Computing_ 14 (4): 783–99. doi:[10.1137/0914050][@higham:1993a].
    193 
    194 </section>
    195 
    196 <!-- /.references -->
    197 
    198 <section class="links">
    199 
    200 [@stdlib/array/float64]: https://www.npmjs.com/package/@stdlib/array-float64
    201 
    202 [mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray
    203 
    204 [@higham:1993a]: https://doi.org/10.1137/0914050
    205 
    206 </section>
    207 
    208 <!-- /.links -->