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author | Yann Herklotz <git@yannherklotz.com> | 2020-08-13 23:24:40 +0100 |
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committer | Yann Herklotz <git@yannherklotz.com> | 2020-08-13 23:24:40 +0100 |
commit | 045c0dc29fc31a8d3f15da8b3130dbc4706ea581 (patch) | |
tree | 56e9eb2ec6c318648e47c43d6b8abb2458ae236e /benchmarks/polybench-syn/data-mining | |
parent | 3971466fbdd9aa1883a4468de3d67fdf90fee02d (diff) | |
download | vericert-kvx-045c0dc29fc31a8d3f15da8b3130dbc4706ea581.tar.gz vericert-kvx-045c0dc29fc31a8d3f15da8b3130dbc4706ea581.zip |
Add modified polybench benchmarks
Diffstat (limited to 'benchmarks/polybench-syn/data-mining')
-rw-r--r-- | benchmarks/polybench-syn/data-mining/covariance.c | 108 |
1 files changed, 108 insertions, 0 deletions
diff --git a/benchmarks/polybench-syn/data-mining/covariance.c b/benchmarks/polybench-syn/data-mining/covariance.c new file mode 100644 index 0000000..63f2320 --- /dev/null +++ b/benchmarks/polybench-syn/data-mining/covariance.c @@ -0,0 +1,108 @@ +/** + * This version is stamped on May 10, 2016 + * + * Contact: + * Louis-Noel Pouchet <pouchet.ohio-state.edu> + * Tomofumi Yuki <tomofumi.yuki.fr> + * + * Web address: http://polybench.sourceforge.net + */ +/* covariance.c: this file is part of PolyBench/C */ + +#define plus(i) i = i + ONE +static +void init_array (int m, int n, + int *float_n, + int data[ 32 + 0][28 + 0]) +{ + int i, j; + int ONE = 1; + int DIV = 28; + + *float_n = (int)n; + + for (i = 0; i < 32; plus(i)) + for (j = 0; j < 28; plus(j)) + data[i][j] = ((int) i*j) / DIV; +} + + + + +static +int print_array(int m, + int cov[ 28 + 0][28 + 0]) + +{ + int i, j; + int ONE = 1; + int res = 0; + for (i = 0; i < m; plus(i)) + for (j = 0; j < m; plus(j)) { + res ^= cov[i][j]; + } + return res; +} + + + + +static +void kernel_covariance(int m, int n, + int float_n, + int data[ 32 + 0][28 + 0], + int cov[ 28 + 0][28 + 0], + int mean[ 28 + 0]) +{ + int i, j, k; + int ONE = 1; + +#pragma scop + for (j = 0; j < m; plus(j)) + { + mean[j] = 0; + for (i = 0; i < n; plus(i)) + mean[j] += data[i][j]; + mean[j] /= float_n; + } + + for (i = 0; i < n; plus(i)) + for (j = 0; j < m; plus(j)) + data[i][j] -= mean[j]; + + for (i = 0; i < m; plus(i)) + for (j = i; j < m; plus(j)) + { + cov[i][j] = 0; + for (k = 0; k < n; plus(k)) + cov[i][j] += data[k][i] * data[k][j]; + cov[i][j] /= (float_n - ONE); + cov[j][i] = cov[i][j]; + } +#pragma endscop + +} + + +int main() +{ + + int n = 32; + int m = 28; + + + int float_n; + int data[32 + 0][28 + 0]; + int mean[28 + 0]; + int cov[28 + 0][28 + 0]; + + init_array (m, n, &float_n, data); + + kernel_covariance (m, n, float_n, + data, + cov, + mean); + + return print_array(m, cov); + +} |