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diff --git a/dis/Matrix/ver1/matrix.c b/dis/Matrix/ver1/matrix.c
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+/*
+ *  Sample code for the DIS Matrix Stressmark
+ *
+ * This source code is the completely correct source code based on 
+ * the example codes provided by Atlantic Aerospace Division, Titan 
+ * Systems Corporation, 2000.
+ * 
+ * If you just compile and generate the executables from this source 
+ * code, this code would be enough. However, if you wish to get a complete 
+ * understanding of this stressmark, it is strongly suggested that you
+ * read the Benchmark Analysis and Specifications Document Version 1.0
+ * before going on since the detailed comments are given in this documents.
+ * the comments are not repeated here.
+ */
+
+/*
+ *  The Sparse Matrix Storage is implemented by Compact Row Storage Scheme
+ *  In the code, the data is first generated by randomNonzeroFloat()
+ *  the data is first stored in a full-space matrix with size of dim*dim
+ *  then the data is transfered to the Compact Row Matrix, 
+ *  the data value is kept in *value,
+ *  the columns corresponding to the value are stored in *col_ind,
+ *  the start element of each row is stored in *row_start.
+ */
+ 
+/* 
+ * Please note: 
+ * the total number of data is numberNonzero +dim
+ * among which, NumberNonzero because this is symmetric matrix
+ * dim because the diagonal elements
+ */
+
+#include <stdio.h>
+#include <math.h>
+#include <stdlib.h>
+#include <time.h>
+#include <assert.h>
+#include "DISstressmarkRNG.h"
+
+#define MIN_SEED -2147483647
+#define MAX_SEED -1
+#define MIN_DIM  1
+#define MAX_DIM  32768
+#define MAX_ITERATIONS 65536
+#define MIN_TOLERANCE 0.000007
+#define MAX_TOLERANCE 0.5
+#define MIN_NUMBER   -3.4e10/dim
+#define MAX_NUMBER 3.4e10/dim
+#define EPSI   1.0e-10
+#define MIN_DIG_NUMBER 1.0e-10
+#define MAX_DIG_NUMBER 3.4e10
+
+/*
+ *  External variable, dimension
+ */
+
+static int dim;
+
+/*      
+ *  matrix * vector     
+ */
+
+double  *matrixMulvector(double *value, 
+                           int *col_ind, 
+                           int *row_start,
+                           double  *vector)
+{  
+  int l, ll;
+  double  *out;
+  double  sum;
+  int tmp_rs, tmp_re;
+  
+  out = (double *)malloc(dim*sizeof(double));
+ 
+  for (l=0; l<dim; l++){  
+     *(out + l) = 0;
+     tmp_rs = row_start[l];
+    
+     if (tmp_rs != -1){
+      tmp_re = row_start[l+1];   /*
+                                  *get the start and ending elements of 
+                                  *  each row
+                                 */
+      for (ll=tmp_rs; ll<tmp_re; ll++){
+        *(out + l) += value[ll]*vector[col_ind[ll]];
+      }
+    }
+  }
+  return out;
+}
+
+
+/*
+ *    vector1 - vector2
+ */
+
+double  *vectorSub(double  *vector1, double  *vector2){
+
+  int l;
+  double  *vector;
+  vector = (double  *)malloc(dim*sizeof(double ));
+  for (l=0; l<dim; l++){
+    *(vector + l) = *(vector1 + l) - *(vector2 + l);
+  }
+  return vector;
+}
+
+
+/*
+ * vector1 + vector2
+ */
+
+double  *vectorAdd(double  *vector1, double  *vector2){
+
+  int l;
+  double  *vector;
+
+  vector = (double  *)malloc(dim*sizeof(double ));
+
+  for (l=0; l<dim; l++){
+    *(vector + l) = *(vector1 + l) + *(vector2 + l);
+  }
+  return vector;
+} 
+
+/* 
+ * vector1 * vector2
+ */
+
+double  vectorMul(double  *vector1, double  *vector2){
+
+  int l;
+  double  product;
+
+  product = 0;
+
+  for (l=0; l<dim; l++){
+    product += (*(vector1 + l))*(*(vector2 + l));
+
+  }
+  return product;
+} 
+
+/*
+ * /vector/
+ */
+
+double  vectorValue(double  *vector){
+
+  double  value;
+  int l;
+
+  value = 0;
+
+  for (l=0; l<dim; l++){
+    value += (*(vector + l)) * (*(vector + l));
+  }
+
+  return (sqrt(value));
+}
+
+/*
+ * transpose(vector)
+ * In fact, we return the original vector here
+ */
+
+double  *transpose(double  *vector){
+
+  double  *vect;
+  int l;
+
+  vect = (double  *)malloc(dim*sizeof(double ));
+
+  for (l=0; l<dim; l++){
+    *(vect+l) = *(vector+l);
+  }
+  return vect;
+}
+
+/*
+ * value * <vector>
+ */
+double  *valueMulvector(double  value, double  *vector){
+
+  int l;
+  double  *vect;
+    int lll;
+    double sum;
+
+  vect = (double  *) malloc(dim * sizeof(double ));
+
+  for (l=0; l<dim; l++){
+    *(vect + l) = (*(vector + l)) * value;
+  }
+
+  return vect;
+}
+  
+/*
+ * generate the data distributed sparsely in matrix
+ */
+
+void initMatrix(double  *matrix, int dim, int numberNonzero){
+  
+  int k, l, ll;
+  int i, j;
+
+  int lll;
+  double sum;
+
+  for (k=0; k< dim*dim; k++){
+    *(matrix + k) = 0;
+  }
+
+  for (l=0; l<numberNonzero/2; l++){
+
+    i = randomUInt(1, dim-1);
+    j = randomUInt(0, i-1);
+