当尺寸变大时，会出现矩阵计算错误

我正在运行一个代码，其中我只创建了两个矩阵：一个矩阵的维度为arows x nsame，另一个矩阵维度为nsame x bcols。结果是一个维度数组arows x bcols。使用BLAS实现这一点相当简单，当使用以下带有OpenMPI的主从模型时，以下代码似乎可以正常工作：`

#include <iostream>
#include <stdio.h>
#include <iostream>
#include <cmath>
#include <mpi.h>
#include <gsl/gsl_blas.h>
using namespace std;`
int main(int argc, char** argv){
int noprocs, nid;
MPI_Status status;
MPI_Init(&argc, &argv);
MPI_Comm_rank(MPI_COMM_WORLD, &nid);
MPI_Comm_size(MPI_COMM_WORLD, &noprocs);
int master = 0;
const int nsame = 500; //must be same if matrices multiplied together = acols = brows
const int arows = 500;
const int bcols = 527; //works for 500 x 500 x 527 and 6000 x 100 x 36
int rowsent;
double buff[nsame];
double b[nsame*bcols];
double c[arows][bcols];
double CC[1*bcols]; //here ncols corresponds to numbers of rows for matrix b
for (int i = 0; i < bcols; i++){
CC[i] = 0.;
}; 
// Master part
if (nid == master ) { 
double a [arows][nsame]; //creating identity matrix of dimensions arows x nsame (it is I if arows = nsame)
for (int i = 0; i < arows; i++){
for (int j = 0; j < nsame; j++){
if (i == j)
a[i][j] = 1.;
else
a[i][j] = 0.;
}
}
double b[nsame*bcols];//here ncols corresponds to numbers of rows for matrix b
for (int i = 0; i < (nsame*bcols); i++){
b[i] = (10.*i + 3.)/(3.*i - 2.) ;
}; 
MPI_Bcast(b,nsame*bcols, MPI_DOUBLE_PRECISION, master, MPI_COMM_WORLD);  
rowsent=0;
for (int i=1; i < (noprocs); i++) {  
// Note A is a 2D array so A[rowsent]=&A[rowsent][0]
MPI_Send(a[rowsent], nsame, MPI_DOUBLE_PRECISION,i,rowsent+1,MPI_COMM_WORLD);
rowsent++; 
}
for (int i=0; i<arows; i++) { 
MPI_Recv(CC, bcols, MPI_DOUBLE_PRECISION, MPI_ANY_SOURCE, MPI_ANY_TAG,
MPI_COMM_WORLD, &status); 
int sender = status.MPI_SOURCE;
int anstype = status.MPI_TAG;            //row number+1
int IND_I = 0;
while (IND_I < bcols){
c[anstype - 1][IND_I] = CC[IND_I]; 
IND_I++;
}
if (rowsent < arows) {
MPI_Send(a[rowsent], nsame,MPI_DOUBLE_PRECISION,sender,rowsent+1,MPI_COMM_WORLD);
rowsent++; 
}
else {       // tell sender no more work to do via a 0 TAG
MPI_Send(MPI_BOTTOM,0,MPI_DOUBLE_PRECISION,sender,0,MPI_COMM_WORLD);
}
}
}
// Slave part
else { 
MPI_Bcast(b,nsame*bcols, MPI_DOUBLE_PRECISION, master, MPI_COMM_WORLD); 
MPI_Recv(buff,nsame,MPI_DOUBLE_PRECISION,master,MPI_ANY_TAG,MPI_COMM_WORLD,&status); 
while(status.MPI_TAG != 0) {
int crow = status.MPI_TAG; 
gsl_matrix_view AAAA = gsl_matrix_view_array(buff, 1, nsame);
gsl_matrix_view BBBB = gsl_matrix_view_array(b, nsame, bcols);
gsl_matrix_view CCCC = gsl_matrix_view_array(CC, 1, bcols);
/* Compute C = A B */
gsl_blas_dgemm (CblasNoTrans, CblasNoTrans, 1.0, &AAAA.matrix, &BBBB.matrix,
0.0, &CCCC.matrix); 
MPI_Send(CC,bcols,MPI_DOUBLE_PRECISION, master, crow, MPI_COMM_WORLD);
MPI_Recv(buff,nsame,MPI_DOUBLE_PRECISION,master,MPI_ANY_TAG,MPI_COMM_WORLD,&status); 
}
}
// output c here on master node //uncomment the below lines if I wish to see the output
//    if (nid == master){
//        if (rowsent == arows){
//            //            cout << rowsent;
//            int IND_F = 0;
//            while (IND_F < arows){
//                int IND_K = 0;
//                while (IND_K < bcols){
//                    cout << "[" << IND_F << "]" << "[" << IND_K << "] = " << c[IND_F][IND_K] << " ";
//                    IND_K++;
//                }
//                cout << "n";
//                IND_F++;
//            }
//        }
//    }
MPI_Finalize();
//free any allocated space here
return 0;
};

现在看起来奇怪的是，当我增加矩阵的大小(例如，从nsame＝500到nsame＝501)时，代码就不再工作了。我收到以下错误：

mpirun noticed that process rank 0 with PID 0 on node Users-MacBook-Air exited on signal 11 (Segmentation fault: 11).

我在矩阵的其他大小组合中尝试过这一点，矩阵本身的大小似乎总是有一个上限(这似乎取决于我如何改变不同的维度本身)。我也尝试过修改矩阵本身的值，尽管这似乎不会改变任何东西。我意识到在我的例子中有其他方法可以初始化矩阵(例如，使用向量)，但我只是想知道为什么我目前的乘以任意大小矩阵的方案似乎只在一定程度上有效。