SingleSource/Benchmarks/Polybench/datamining/correlation/correlation.c - third_party/llvm-test-suite - Git at Google

 /**
  * correlation.c: This file is part of the PolyBench/C 3.2 test suite.
  *
  *
  * Contact: Louis-Noel Pouchet <pouchet@cse.ohio-state.edu>
  * Web address: http://polybench.sourceforge.net
  */
 #include <stdio.h>
 #include <unistd.h>
 #include <string.h>
 #include <math.h>

 /* Include polybench common header. */
 #include "../../utilities/polybench.h"

 /* Include benchmark-specific header. */
 /* Default data type is double, default size is 4000. */
 #include "correlation.h"


 /* Array initialization. */
 static
 void init_array (int m,
 		 int n,
 		 DATA_TYPE *float_n,
 		 DATA_TYPE POLYBENCH_2D(data,M,N,m,n))
 {
 #pragma STDC FP_CONTRACT OFF
   int i, j;

   *float_n = 1.2;

   for (i = 0; i < m; i++)
     for (j = 0; j < n; j++)
       data[i][j] = ((DATA_TYPE) i*j) / M;
 }


 /* DCE code. Must scan the entire live-out data.
    Can be used also to check the correctness of the output. */
 static
 void print_array(int m,
 		 DATA_TYPE POLYBENCH_2D(symmat,M,M,m,m))

 {
   int i, j;
   char *printmat = malloc(m*16 + 1); printmat[m*16] = 0;

   for (i = 0; i < m; i++) {
     for (j = 0; j < m; j++) {
       print_element(symmat[i][j], j*16, printmat);
     }
     fputs(printmat, stderr);
   }
   free(printmat);
 }


 /* Main computational kernel. The whole function will be timed,
    including the call and return. */
 static
 void kernel_correlation(int m, int n,
 			DATA_TYPE float_n,
 			DATA_TYPE POLYBENCH_2D(data,M,N,m,n),
 			DATA_TYPE POLYBENCH_2D(symmat,M,M,m,m),
 			DATA_TYPE POLYBENCH_1D(mean,M,m),
 			DATA_TYPE POLYBENCH_1D(stddev,M,m))
 {
   int i, j, j1, j2;

   DATA_TYPE eps = 0.1f;

 #define sqrt_of_array_cell(x,j) sqrt(x[j])

 #pragma scop
   /* Determine mean of column vectors of input data matrix */
   for (j = 0; j < _PB_M; j++)
     {
       mean[j] = 0.0;
       for (i = 0; i < _PB_N; i++)
 	mean[j] += data[i][j];
       mean[j] /= float_n;
     }

   /* Determine standard deviations of column vectors of data matrix. */
   for (j = 0; j < _PB_M; j++)
     {
       stddev[j] = 0.0;
       for (i = 0; i < _PB_N; i++)
 	stddev[j] += (data[i][j] - mean[j]) * (data[i][j] - mean[j]);
       stddev[j] /= float_n;
       stddev[j] = sqrt_of_array_cell(stddev, j);
       /* The following in an inelegant but usual way to handle
 	 near-zero std. dev. values, which below would cause a zero-
 	 divide. */
       stddev[j] = stddev[j] <= eps ? 1.0 : stddev[j];
     }

   /* Center and reduce the column vectors. */
   for (i = 0; i < _PB_N; i++)
     for (j = 0; j < _PB_M; j++)
       {
 	data[i][j] -= mean[j];
 	data[i][j] /= sqrt(float_n) * stddev[j];
       }

   /* Calculate the m * m correlation matrix. */
   for (j1 = 0; j1 < _PB_M-1; j1++)
     {
       symmat[j1][j1] = 1.0;
       for (j2 = j1+1; j2 < _PB_M; j2++)
 	{
 	  symmat[j1][j2] = 0.0;
 	  for (i = 0; i < _PB_N; i++)
 	    symmat[j1][j2] += (data[i][j1] * data[i][j2]);
 	  symmat[j2][j1] = symmat[j1][j2];
 	}
     }
   symmat[_PB_M-1][_PB_M-1] = 1.0;
 #pragma endscop

 }

 #if !FMA_DISABLED
 // NOTE: FMA_DISABLED is true for targets where FMA contraction causes
 // discrepancies which cause the accuracy checks to fail.
 // In this case, the test runs with the option -ffp-contract=off
 static void
 kernel_correlation_StrictFP(int m, int n,
                             DATA_TYPE float_n,
                             DATA_TYPE POLYBENCH_2D(data,M,N,m,n),
                             DATA_TYPE POLYBENCH_2D(symmat,M,M,m,m),
                             DATA_TYPE POLYBENCH_1D(mean,M,m),
                             DATA_TYPE POLYBENCH_1D(stddev,M,m))
 {
 #pragma STDC FP_CONTRACT OFF
   int i, j, j1, j2;

   DATA_TYPE eps = 0.1f;

 #define sqrt_of_array_cell(x,j) sqrt(x[j])

   /* Determine mean of column vectors of input data matrix */
   for (j = 0; j < _PB_M; j++)
     {
       mean[j] = 0.0;
       for (i = 0; i < _PB_N; i++)
 	mean[j] += data[i][j];
       mean[j] /= float_n;
     }

   /* Determine standard deviations of column vectors of data matrix. */
   for (j = 0; j < _PB_M; j++)
     {
       stddev[j] = 0.0;
       for (i = 0; i < _PB_N; i++)
 	stddev[j] += (data[i][j] - mean[j]) * (data[i][j] - mean[j]);
       stddev[j] /= float_n;
       stddev[j] = sqrt_of_array_cell(stddev, j);
       /* The following in an inelegant but usual way to handle
 	 near-zero std. dev. values, which below would cause a zero-
 	 divide. */
       stddev[j] = stddev[j] <= eps ? 1.0 : stddev[j];
     }

   /* Center and reduce the column vectors. */
   for (i = 0; i < _PB_N; i++)
     for (j = 0; j < _PB_M; j++)
       {
 	data[i][j] -= mean[j];
 	data[i][j] /= sqrt(float_n) * stddev[j];
       }

   /* Calculate the m * m correlation matrix. */
   for (j1 = 0; j1 < _PB_M-1; j1++)
     {
       symmat[j1][j1] = 1.0;
       for (j2 = j1+1; j2 < _PB_M; j2++)
 	{
 	  symmat[j1][j2] = 0.0;
 	  for (i = 0; i < _PB_N; i++)
 	    symmat[j1][j2] += (data[i][j1] * data[i][j2]);
 	  symmat[j2][j1] = symmat[j1][j2];
 	}
     }
   symmat[_PB_M-1][_PB_M-1] = 1.0;
 }

 /* Return 0 when one of the elements of arrays A and B do not match within the
    allowed FP_ABSTOLERANCE.  Return 1 when all elements match.  */
 static inline int
 check_FP(int m,
          DATA_TYPE POLYBENCH_2D(A,M,M,m,m),
          DATA_TYPE POLYBENCH_2D(B,M,M,m,m)) {
   int i, j;
   double AbsTolerance = FP_ABSTOLERANCE;
   for (i = 0; i < _PB_M; i++)
     for (j = 0; j < _PB_M; j++)
       {
         double V1 = A[i][j];
         double V2 = B[i][j];
         double Diff = fabs(V1 - V2);
         if (Diff > AbsTolerance) {
           fprintf(stderr, "A[%d][%d] = %lf and B[%d][%d] = %lf differ more than"
                   " FP_ABSTOLERANCE = %lf\n", i, j, V1, i, j, V2, AbsTolerance);
           return 0;
         }
       }

   /* All elements are within the allowed FP_ABSTOLERANCE error margin.  */
   return 1;
 }
 #endif

 int main(int argc, char** argv)
 {
   /* Retrieve problem size. */
   int n = N;
   int m = M;

   /* Variable declaration/allocation. */
   DATA_TYPE float_n;
   POLYBENCH_2D_ARRAY_DECL(data,DATA_TYPE,M,N,m,n);
   POLYBENCH_2D_ARRAY_DECL(symmat,DATA_TYPE,M,M,m,m);
 #if !FMA_DISABLED
   POLYBENCH_2D_ARRAY_DECL(symmat_StrictFP,DATA_TYPE,M,M,m,m);
 #endif
   POLYBENCH_1D_ARRAY_DECL(mean,DATA_TYPE,M,m);
   POLYBENCH_1D_ARRAY_DECL(stddev,DATA_TYPE,M,m);

   /* Initialize array(s). */
   init_array (m, n, &float_n, POLYBENCH_ARRAY(data));

   /* Start timer. */
   polybench_start_instruments;

   /* Run kernel. */
   kernel_correlation (m, n, float_n,
 		      POLYBENCH_ARRAY(data),
 		      POLYBENCH_ARRAY(symmat),
 		      POLYBENCH_ARRAY(mean),
 		      POLYBENCH_ARRAY(stddev));

   /* Stop and print timer. */
   polybench_stop_instruments;
   polybench_print_instruments;

 #if FMA_DISABLED
   /* Prevent dead-code elimination. All live-out data must be printed
      by the function call in argument. */
   polybench_prevent_dce(print_array(m, POLYBENCH_ARRAY(symmat)));
 #else
   init_array (m, n, &float_n, POLYBENCH_ARRAY(data));
   kernel_correlation (m, n, float_n,
 		      POLYBENCH_ARRAY(data),
 		      POLYBENCH_ARRAY(symmat_StrictFP),
 		      POLYBENCH_ARRAY(mean),
 		      POLYBENCH_ARRAY(stddev));
   if (!check_FP(m, POLYBENCH_ARRAY(symmat), POLYBENCH_ARRAY(symmat_StrictFP)))
     return 1;

   /* Prevent dead-code elimination. All live-out data must be printed
      by the function call in argument. */
   polybench_prevent_dce(print_array(m, POLYBENCH_ARRAY(symmat_StrictFP)));
 #endif

   /* Be clean. */
   POLYBENCH_FREE_ARRAY(data);
   POLYBENCH_FREE_ARRAY(symmat);
 #if !FMA_DISABLED
   POLYBENCH_FREE_ARRAY(symmat_StrictFP);
 #endif
   POLYBENCH_FREE_ARRAY(mean);
   POLYBENCH_FREE_ARRAY(stddev);

   return 0;
 }
	/**
	* correlation.c: This file is part of the PolyBench/C 3.2 test suite.
	*
	*
	* Contact: Louis-Noel Pouchet <pouchet@cse.ohio-state.edu>
	* Web address: http://polybench.sourceforge.net
	*/
	#include <stdio.h>
	#include <unistd.h>
	#include <string.h>
	#include <math.h>

	/* Include polybench common header. */
	#include "../../utilities/polybench.h"

	/* Include benchmark-specific header. */
	/* Default data type is double, default size is 4000. */
	#include "correlation.h"


	/* Array initialization. */
	static
	void init_array (int m,
	int n,
	DATA_TYPE *float_n,
	DATA_TYPE POLYBENCH_2D(data,M,N,m,n))
	{
	#pragma STDC FP_CONTRACT OFF
	int i, j;

	*float_n = 1.2;

	for (i = 0; i < m; i++)
	for (j = 0; j < n; j++)
	data[i][j] = ((DATA_TYPE) i*j) / M;
	}


	/* DCE code. Must scan the entire live-out data.
	Can be used also to check the correctness of the output. */
	static
	void print_array(int m,
	DATA_TYPE POLYBENCH_2D(symmat,M,M,m,m))

	{
	int i, j;
	char printmat = malloc(m16 + 1); printmat[m*16] = 0;

	for (i = 0; i < m; i++) {
	for (j = 0; j < m; j++) {
	print_element(symmat[i][j], j*16, printmat);
	}
	fputs(printmat, stderr);
	}
	free(printmat);
	}


	/* Main computational kernel. The whole function will be timed,
	including the call and return. */
	static
	void kernel_correlation(int m, int n,
	DATA_TYPE float_n,
	DATA_TYPE POLYBENCH_2D(data,M,N,m,n),
	DATA_TYPE POLYBENCH_2D(symmat,M,M,m,m),
	DATA_TYPE POLYBENCH_1D(mean,M,m),
	DATA_TYPE POLYBENCH_1D(stddev,M,m))
	{
	int i, j, j1, j2;

	DATA_TYPE eps = 0.1f;

	#define sqrt_of_array_cell(x,j) sqrt(x[j])

	#pragma scop
	/* Determine mean of column vectors of input data matrix */
	for (j = 0; j < _PB_M; j++)
	{
	mean[j] = 0.0;
	for (i = 0; i < _PB_N; i++)
	mean[j] += data[i][j];
	mean[j] /= float_n;
	}

	/* Determine standard deviations of column vectors of data matrix. */
	for (j = 0; j < _PB_M; j++)
	{
	stddev[j] = 0.0;
	for (i = 0; i < _PB_N; i++)
	stddev[j] += (data[i][j] - mean[j]) * (data[i][j] - mean[j]);
	stddev[j] /= float_n;
	stddev[j] = sqrt_of_array_cell(stddev, j);
	/* The following in an inelegant but usual way to handle
	near-zero std. dev. values, which below would cause a zero-
	divide. */
	stddev[j] = stddev[j] <= eps ? 1.0 : stddev[j];
	}

	/* Center and reduce the column vectors. */
	for (i = 0; i < _PB_N; i++)
	for (j = 0; j < _PB_M; j++)
	{
	data[i][j] -= mean[j];
	data[i][j] /= sqrt(float_n) * stddev[j];
	}

	/* Calculate the m * m correlation matrix. */
	for (j1 = 0; j1 < _PB_M-1; j1++)
	{
	symmat[j1][j1] = 1.0;
	for (j2 = j1+1; j2 < _PB_M; j2++)
	{
	symmat[j1][j2] = 0.0;
	for (i = 0; i < _PB_N; i++)
	symmat[j1][j2] += (data[i][j1] * data[i][j2]);
	symmat[j2][j1] = symmat[j1][j2];
	}
	}
	symmat[_PB_M-1][_PB_M-1] = 1.0;
	#pragma endscop

	}

	#if !FMA_DISABLED
	// NOTE: FMA_DISABLED is true for targets where FMA contraction causes
	// discrepancies which cause the accuracy checks to fail.
	// In this case, the test runs with the option -ffp-contract=off
	static void
	kernel_correlation_StrictFP(int m, int n,
	DATA_TYPE float_n,
	DATA_TYPE POLYBENCH_2D(data,M,N,m,n),
	DATA_TYPE POLYBENCH_2D(symmat,M,M,m,m),
	DATA_TYPE POLYBENCH_1D(mean,M,m),
	DATA_TYPE POLYBENCH_1D(stddev,M,m))
	{
	#pragma STDC FP_CONTRACT OFF
	int i, j, j1, j2;

	DATA_TYPE eps = 0.1f;

	#define sqrt_of_array_cell(x,j) sqrt(x[j])

	/* Determine mean of column vectors of input data matrix */
	for (j = 0; j < _PB_M; j++)
	{
	mean[j] = 0.0;
	for (i = 0; i < _PB_N; i++)
	mean[j] += data[i][j];
	mean[j] /= float_n;
	}

	/* Determine standard deviations of column vectors of data matrix. */
	for (j = 0; j < _PB_M; j++)
	{
	stddev[j] = 0.0;
	for (i = 0; i < _PB_N; i++)
	stddev[j] += (data[i][j] - mean[j]) * (data[i][j] - mean[j]);
	stddev[j] /= float_n;
	stddev[j] = sqrt_of_array_cell(stddev, j);
	/* The following in an inelegant but usual way to handle
	near-zero std. dev. values, which below would cause a zero-
	divide. */
	stddev[j] = stddev[j] <= eps ? 1.0 : stddev[j];
	}

	/* Center and reduce the column vectors. */
	for (i = 0; i < _PB_N; i++)
	for (j = 0; j < _PB_M; j++)
	{
	data[i][j] -= mean[j];
	data[i][j] /= sqrt(float_n) * stddev[j];
	}

	/* Calculate the m * m correlation matrix. */
	for (j1 = 0; j1 < _PB_M-1; j1++)
	{
	symmat[j1][j1] = 1.0;
	for (j2 = j1+1; j2 < _PB_M; j2++)
	{
	symmat[j1][j2] = 0.0;
	for (i = 0; i < _PB_N; i++)
	symmat[j1][j2] += (data[i][j1] * data[i][j2]);
	symmat[j2][j1] = symmat[j1][j2];
	}
	}
	symmat[_PB_M-1][_PB_M-1] = 1.0;
	}

	/* Return 0 when one of the elements of arrays A and B do not match within the
	allowed FP_ABSTOLERANCE. Return 1 when all elements match. */
	static inline int
	check_FP(int m,
	DATA_TYPE POLYBENCH_2D(A,M,M,m,m),
	DATA_TYPE POLYBENCH_2D(B,M,M,m,m)) {
	int i, j;
	double AbsTolerance = FP_ABSTOLERANCE;
	for (i = 0; i < _PB_M; i++)
	for (j = 0; j < _PB_M; j++)
	{
	double V1 = A[i][j];
	double V2 = B[i][j];
	double Diff = fabs(V1 - V2);
	if (Diff > AbsTolerance) {
	fprintf(stderr, "A[%d][%d] = %lf and B[%d][%d] = %lf differ more than"
	" FP_ABSTOLERANCE = %lf\n", i, j, V1, i, j, V2, AbsTolerance);
	return 0;
	}
	}

	/* All elements are within the allowed FP_ABSTOLERANCE error margin. */
	return 1;
	}
	#endif

	int main(int argc, char** argv)
	{
	/* Retrieve problem size. */
	int n = N;
	int m = M;

	/* Variable declaration/allocation. */
	DATA_TYPE float_n;
	POLYBENCH_2D_ARRAY_DECL(data,DATA_TYPE,M,N,m,n);
	POLYBENCH_2D_ARRAY_DECL(symmat,DATA_TYPE,M,M,m,m);
	#if !FMA_DISABLED
	POLYBENCH_2D_ARRAY_DECL(symmat_StrictFP,DATA_TYPE,M,M,m,m);
	#endif
	POLYBENCH_1D_ARRAY_DECL(mean,DATA_TYPE,M,m);
	POLYBENCH_1D_ARRAY_DECL(stddev,DATA_TYPE,M,m);

	/* Initialize array(s). */
	init_array (m, n, &float_n, POLYBENCH_ARRAY(data));

	/* Start timer. */
	polybench_start_instruments;

	/* Run kernel. */
	kernel_correlation (m, n, float_n,
	POLYBENCH_ARRAY(data),
	POLYBENCH_ARRAY(symmat),
	POLYBENCH_ARRAY(mean),
	POLYBENCH_ARRAY(stddev));

	/* Stop and print timer. */
	polybench_stop_instruments;
	polybench_print_instruments;

	#if FMA_DISABLED
	/* Prevent dead-code elimination. All live-out data must be printed
	by the function call in argument. */
	polybench_prevent_dce(print_array(m, POLYBENCH_ARRAY(symmat)));
	#else
	init_array (m, n, &float_n, POLYBENCH_ARRAY(data));
	kernel_correlation (m, n, float_n,
	POLYBENCH_ARRAY(data),
	POLYBENCH_ARRAY(symmat_StrictFP),
	POLYBENCH_ARRAY(mean),
	POLYBENCH_ARRAY(stddev));
	if (!check_FP(m, POLYBENCH_ARRAY(symmat), POLYBENCH_ARRAY(symmat_StrictFP)))
	return 1;

	/* Prevent dead-code elimination. All live-out data must be printed
	by the function call in argument. */
	polybench_prevent_dce(print_array(m, POLYBENCH_ARRAY(symmat_StrictFP)));
	#endif

	/* Be clean. */
	POLYBENCH_FREE_ARRAY(data);
	POLYBENCH_FREE_ARRAY(symmat);
	#if !FMA_DISABLED
	POLYBENCH_FREE_ARRAY(symmat_StrictFP);
	#endif
	POLYBENCH_FREE_ARRAY(mean);
	POLYBENCH_FREE_ARRAY(stddev);

	return 0;
	}