time-to-botec

Benchmark sampling in different programming languages
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dnannsumpw.c (4336B)


      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 #include "stdlib/blas/ext/base/dnannsumpw.h"
     20 #include <stdint.h>
     21 
     22 /**
     23 * Computes the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using pairwise summation.
     24 *
     25 * @private
     26 * @param N       number of indexed elements
     27 * @param X       input array
     28 * @param stride  stride length
     29 * @param n       pointer for storing the number of non-NaN elements
     30 * @return        output value
     31 */
     32 static double sumpw( const int64_t N, const double *X, const int64_t stride, int64_t *n ) {
     33 	double *xp1;
     34 	double *xp2;
     35 	double sum;
     36 	int64_t ix;
     37 	int64_t M;
     38 	int64_t m;
     39 	int64_t i;
     40 	double s0;
     41 	double s1;
     42 	double s2;
     43 	double s3;
     44 	double s4;
     45 	double s5;
     46 	double s6;
     47 	double s7;
     48 	double v;
     49 
     50 	if ( N <= 0 ) {
     51 		return 0.0;
     52 	}
     53 	if ( N == 1 || stride == 0 ) {
     54 		v = X[ 0 ];
     55 		if ( v == v ) {
     56 			*n += 1;
     57 			return v;
     58 		}
     59 		return 0.0;
     60 	}
     61 	if ( stride < 0 ) {
     62 		ix = (1-N) * stride;
     63 	} else {
     64 		ix = 0;
     65 	}
     66 	if ( N < 8 ) {
     67 		// Use simple summation...
     68 		sum = 0.0;
     69 		for ( i = 0; i < N; i++ ) {
     70 			v = X[ ix ];
     71 			if ( v == v ) {
     72 				sum += v;
     73 				*n += 1;
     74 			}
     75 			ix += stride;
     76 		}
     77 		return sum;
     78 	}
     79 	// Blocksize for pairwise summation: 128 (NOTE: decreasing the blocksize decreases rounding error as more pairs are summed, but also decreases performance. Because the inner loop is unrolled eight times, the blocksize is effectively `16`.)
     80 	if ( N <= 128 ) {
     81 		// Sum a block with 8 accumulators (by loop unrolling, we lower the effective blocksize to 16)...
     82 		s0 = 0.0;
     83 		s1 = 0.0;
     84 		s2 = 0.0;
     85 		s3 = 0.0;
     86 		s4 = 0.0;
     87 		s5 = 0.0;
     88 		s6 = 0.0;
     89 		s7 = 0.0;
     90 
     91 		M = N % 8;
     92 		for ( i = 0; i < N-M; i += 8 ) {
     93 			v = X[ ix ];
     94 			if ( v == v ) {
     95 				s0 += v;
     96 				*n += 1;
     97 			}
     98 			ix += stride;
     99 			v = X[ ix ];
    100 			if ( v == v ) {
    101 				s1 += v;
    102 				*n += 1;
    103 			}
    104 			ix += stride;
    105 			v = X[ ix ];
    106 			if ( v == v ) {
    107 				s2 += v;
    108 				*n += 1;
    109 			}
    110 			ix += stride;
    111 			v = X[ ix ];
    112 			if ( v == v ) {
    113 				s3 += v;
    114 				*n += 1;
    115 			}
    116 			ix += stride;
    117 			v = X[ ix ];
    118 			if ( v == v ) {
    119 				s4 += v;
    120 				*n += 1;
    121 			}
    122 			ix += stride;
    123 			v = X[ ix ];
    124 			if ( v == v ) {
    125 				s5 += v;
    126 				*n += 1;
    127 			}
    128 			ix += stride;
    129 			v = X[ ix ];
    130 			if ( v == v ) {
    131 				s6 += v;
    132 				*n += 1;
    133 			}
    134 			ix += stride;
    135 			v = X[ ix ];
    136 			if ( v == v ) {
    137 				s7 += v;
    138 				*n += 1;
    139 			}
    140 			ix += stride;
    141 		}
    142 		// Pairwise sum the accumulators:
    143 		sum = ((s0+s1) + (s2+s3)) + ((s4+s5) + (s6+s7));
    144 
    145 		// Clean-up loop...
    146 		for (; i < N; i++ ) {
    147 			v = X[ ix ];
    148 			if ( v == v ) {
    149 				sum += v;
    150 				*n += 1;
    151 			}
    152 			ix += stride;
    153 		}
    154 		return sum;
    155 	}
    156 	// Recurse by dividing by two, but avoiding non-multiples of unroll factor...
    157 	m = N / 2;
    158 	m -= m % 8;
    159 	if ( stride < 0 ) {
    160 		xp1 = (double *)X + ( (m-N)*stride );
    161 		xp2 = (double *)X;
    162 	} else {
    163 		xp1 = (double *)X;
    164 		xp2 = (double *)X + ( m*stride );
    165 	}
    166 	return sumpw( m, xp1, stride, n ) + sumpw( N-m, xp2, stride, n );
    167 }
    168 
    169 /**
    170 * Computes the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using pairwise summation.
    171 *
    172 * ## Method
    173 *
    174 * -   This implementation uses pairwise summation, which accrues rounding error `O(log2 N)` instead of `O(N)`. The recursion depth is also `O(log2 N)`.
    175 *
    176 * ## References
    177 *
    178 * -   Higham, Nicholas J. 1993. "The Accuracy of Floating Point Summation." _SIAM Journal on Scientific Computing_ 14 (4): 783–99. doi:[10.1137/0914050](https://doi.org/10.1137/0914050).
    179 *
    180 * @param N       number of indexed elements
    181 * @param X       input array
    182 * @param stride  stride length
    183 * @param n       pointer for storing the number of non-NaN elements
    184 * @return        output value
    185 */
    186 double stdlib_strided_dnannsumpw( const int64_t N, const double *X, const int64_t stride, int64_t *n ) {
    187 	*n = 0;
    188 	return sumpw( N, X, stride, n );
    189 }