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diff --git a/SD-VBS/benchmarks/pca/src/pca b/SD-VBS/benchmarks/pca/src/pca
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+++ b/SD-VBS/benchmarks/pca/src/pca
diff --git a/SD-VBS/benchmarks/pca/src/pca.c b/SD-VBS/benchmarks/pca/src/pca.c
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+/***********************  Contents  ****************************************
+ * Principal Components Analysis: C, 638 lines. ****************************
+ * Sample input data set (final 36 lines). *********************************
+ ***************************************************************************
+ */
+
+/*********************************/
+/* Principal Components Analysis */
+/*********************************/
+
+/*********************************************************************/
+/* Principal Components Analysis or the Karhunen-Loeve expansion is a
+   classical method for dimensionality reduction or exploratory data
+   analysis.  One reference among many is: F. Murtagh and A. Heck,
+   Multivariate Data Analysis, Kluwer Academic, Dordrecht, 1987.
+
+Author:
+F. Murtagh
+Phone:        + 49 89 32006298 (work)
++ 49 89 965307 (home)
+Earn/Bitnet:  fionn@dgaeso51,  fim@dgaipp1s,  murtagh@stsci
+Span:         esomc1::fionn
+Internet:     murtagh@scivax.stsci.edu
+
+F. Murtagh, Munich, 6 June 1989                                   */   
+/*********************************************************************/
+
+#include <stdio.h>
+#include <string.h>
+#include <math.h>
+
+#define SIGN(a, b) ( (b) < 0 ? -fabs(a) : fabs(a) )
+
+main(argc, argv)
+  int argc;
+  char *argv[];
+
+{
+  FILE *stream;
+  int  n, m,  i, j, k, k2;
+  float **data, **matrix(), **symmat, **symmat2, *vector(), *evals, *interm;
+  void free_matrix(), free_vector(), corcol(), covcol(), scpcol();
+  void tred2(), tqli();
+  float in_value;
+  char option, *strncpy();
+
+  /*********************************************************************
+    Get from command line:
+    input data file name, #rows, #cols, option.
+
+    Open input file: fopen opens the file whose name is stored in the
+    pointer argv[argc-1]; if unsuccessful, error message is printed to
+    stderr.
+   *********************************************************************/
+
+  if (argc !=  5)
+  {
+    printf("Syntax help: PCA filename #rows #cols option\n\n");
+    printf("(filename -- give full path name,\n");
+    printf(" #rows                          \n");
+    printf(" #cols    -- integer values,\n");                  
+    printf(" option   -- R (recommended) for correlation analysis,\n");
+    printf("             V for variance/covariance analysis\n");
+    printf("             S for SSCP analysis.)\n");
+    exit(1);
+  }
+
+  n = atoi(argv[2]);              /* # rows */
+  m = atoi(argv[3]);              /* # columns */
+  strncpy(&option,argv[4],1);     /* Analysis option */
+
+  printf("No. of rows: %d, no. of columns: %d.\n",n,m);
+  printf("Input file: %s.\n",argv[1]);
+
+  if ((stream = fopen(argv[1],"r")) == NULL)
+  {
+    fprintf(stderr, "Program %s : cannot open file %s\n",
+        argv[0], argv[1]);
+    fprintf(stderr, "Exiting to system.");
+    exit(1);
+    /* Note: in versions of DOS prior to 3.0, argv[0] contains the
+       string "C". */
+  }
+
+  /* Now read in data. */
+
+  data = matrix(n, m);  /* Storage allocation for input data */
+
+  for (i = 1; i <= n; i++)
+  {
+    for (j = 1; j <= m; j++)
+    {
+      fscanf(stream, "%f", &in_value);
+      data[i][j] = in_value;
+      printf("at row %d column %d is %lf\n",i,j,data[i][j]);
+    }
+  }
+
+
+
+  /* Check on (part of) input data.
+     for (i = 1; i <= 18; i++) {for (j = 1; j <= 8; j++)  {
+     printf("%7.1f", data[i][j]);  }  printf("\n");  }
+     */
+
+
+
+  symmat = matrix(m, m);  /* Allocation of correlation (etc.) matrix */
+
+  /* Look at analysis option; branch in accordance with this. */
+
+  switch(option)
+  {
+    case 'R':
+    case 'r':
+      printf("Analysis of correlations chosen.\n");
+      corcol(data, n, m, symmat);
+
+      /* Output correlation matrix.
+         for (i = 1; i <= m; i++) {
+         for (j = 1; j <= 8; j++)  {
+         printf("%7.4f", symmat[i][j]);  }
+         printf("\n");  }
+         */
+      break;
+    case 'V':
+    case 'v':
+      printf("Analysis of variances-covariances chosen.\n");
+      covcol(data, n, m, symmat);
+
+      /* Output variance-covariance matrix.
+         for (i = 1; i <= m; i++) {
+         for (j = 1; j <= 8; j++)  {
+         printf("%7.1f", symmat[i][j]);  }
+         printf("\n");  }
+         */
+      break;
+    case 'S':
+    case 's':
+      printf("Analysis of sums-of-squares-cross-products");
+      printf(" matrix chosen.\n");
+      scpcol(data, n, m, symmat);
+
+      /* Output SSCP matrix.
+         for (i = 1; i <= m; i++) {
+         for (j = 1; j <= 8; j++)  {
+         printf("%7.1f", symmat[i][j]);  }
+         printf("\n");  }
+         */
+      break;
+    default:
+      printf("Option: %s\n",option);
+      printf("For option, please type R, V, or S\n");
+      printf("(upper or lower case).\n");
+      printf("Exiting to system.\n");
+      exit(1);
+      break;
+  }
+
+  /*********************************************************************
+    Eigen-reduction
+   **********************************************************************/
+
+  /* Allocate storage for dummy and new vectors. */
+  evals = vector(m);     /* Storage alloc. for vector of eigenvalues */
+  printf("the vector storage size is %d\n",m);
+  interm = vector(m);    /* Storage alloc. for 'intermediate' vector */
+  symmat2 = matrix(m, m);  /* Duplicate of correlation (etc.) matrix */
+  for (i = 1; i <= m; i++) {
+    for (j = 1; j <= m; j++) {
+      symmat2[i][j] = symmat[i][j]; /* Needed below for col. projections */
+    }
+  }
+  tred2(symmat, m, evals, interm);  /* Triangular decomposition */
+  printf("eval value at 0 is %lf\n",evals[0]);
+  printf("eval value at 1 is %lf\n",evals[1]);
+  printf("eval value at 2 is %lf\n",evals[2]);
+
+  printf("m/height is %lf \n",m);
+
+  printf("m/height is %d \n",m);
+  printf("m/height is %d \n",n);
+  printf("m/height is %d \n",n);
+
+
+  tqli(evals, interm, m, symmat);   /* Reduction of sym. trid. matrix */
+  /* evals now contains the eigenvalues,
+     columns of symmat now contain the associated eigenvectors. */
+
+  printf("\nEigenvalues:\n");
+  for (j = m; j >= 1; j--) {
+    printf("%18.5f\n", evals[j]); }
+  printf("\n(Eigenvalues should be strictly positive; limited\n");
+  printf("precision machine arithmetic may affect this.\n");
+  printf("Eigenvalues are often expressed as cumulative\n");
+  printf("percentages, representing the 'percentage variance\n");
+  printf("explained' by the associated axis or principal component.)\n");
+
+  printf("\nEigenvectors:\n");