aboutsummaryrefslogtreecommitdiffstats
diff options
context:
space:
mode:
authorYann Herklotz <git@yannherklotz.com>2020-07-04 12:08:50 +0100
committerYann Herklotz <git@yannherklotz.com>2020-07-04 12:08:50 +0100
commit6613005bf68310eae57f35026ae72a06c5f4cfe5 (patch)
tree889636fe40a3c0b1f55383e8f17d6c012f749c68
parentc7ffca253cf1767ae1416160e1a50bb5450c339f (diff)
parenta0fb7e582f6e844adfaa04e56e7ae7387d043833 (diff)
downloadvericert-kvx-6613005bf68310eae57f35026ae72a06c5f4cfe5.tar.gz
vericert-kvx-6613005bf68310eae57f35026ae72a06c5f4cfe5.zip
Merge branch 'dev-nadesh-proven' of github.com:ymherklotz/CoqUp into dev-nadesh-proven
-rw-r--r--benchmarks/polybench-syn/data-mining/covariance.c108
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);
+
+}