我正在尝试通过对角化来求解薛定ding方程。我在VS2019上使用C ++并使用mkl-lapackage获得特征值和特征向量。整个文件是从LAPACKE_dsyev的intel示例中修改的。 我只是修改了一小部分。但我遇到了:
0x00C86C79有一个未处理的异常(在schro_comp.exe中):0xC00000FD:堆栈溢出(参数:0x00000000,0x00402000)。
我不知道为什么。它是500 * 500矩阵。不大吧?我请人帮忙。
我的代码是:
#include <stdlib.h>
#include <stdio.h>
#include "mkl_lapacke.h"
/* Auxiliary routines prototypes */
extern void print_matrix(char* desc, MKL_INT m, MKL_INT n, double* a, MKL_INT lda);
/* Parameters */
#define N 500//nstep
#define LDA N
#define RMIN -10.0
#define RMAX 10.0
/* Main program */
int main() {
/* Locals */
MKL_INT n = N, lda = LDA, info;
/* Local arrays */
double h = (RMAX - RMIN) / (double(N) + 1.0);
double xi;
double w[N];
double a[LDA * N];
for (int i = 0; i < N; i++) {
xi = RMIN + double(1.0+i) * h;
a[i*(N+1)] = 2.0 / h / h+xi * xi;
if (i==0) {
a[1] = -1.0 / h / h;
}
else if (i == N - 1) {
a[LDA * N-2] =- 1.0 / h / h;
}
else {
a[i *(N + 1)+1] = 2.0 / h / h + xi * xi;
a[i * (N + 1) - 1] = 2.0 / h / h + xi * xi;
}
}
/* Executable statements */
printf("LAPACKE_dsyev (row-major, high-level) Example Program Results\n");
/* Solve eigenproblem */
info = LAPACKE_dsyev(LAPACK_ROW_MAJOR, 'V', 'U', n, a, lda, w);
/* Check for convergence */
if (info > 0) {
printf("The algorithm failed to compute eigenvalues.\n");
exit(1);
}
/* Print eigenvalues */
print_matrix("Eigenvalues", 1, n, w, 1);
/* Print eigenvectors */
print_matrix("Eigenvectors (stored columnwise)", n, n, a, lda);
exit(0);
} /* End of LAPACKE_dsyev Example */
/* Auxiliary routine: printing a matrix */
void print_matrix(char* desc, MKL_INT m, MKL_INT n, double* a, MKL_INT lda) {
MKL_INT i, j;
printf("\n %s\n", desc);
for (i = 0; i < m; i++) {
for (j = 0; j < n; j++) printf(" %6.2f", a[i * lda + j]);
printf("\n");
}
}
我已经纠正了一些错误,但是它仍然存在。...
矩阵类似于:
矩阵的最后一个e_nstep-1
应该是e_nstep-2
。
谢谢所有人的帮助。问题已经解决了。 VS2019上的堆栈空间为1MB。因此。...malloc()
和free()
可以解决此问题。
答案 0 :(得分:1)
问题已解决。谢谢大家的帮助。只需malloc和free就可以解决问题。(VS2019堆栈空间默认为1MB,您也可以控制它。)
#include <stdlib.h>
#include <stdio.h>
#include "mkl_lapacke.h"
/* Auxiliary routines prototypes */
extern void print_matrix(char* desc, MKL_INT m, MKL_INT n, double* a, MKL_INT lda);
/* Parameters */
#define N 500//nstep
#define LDA N
#define RMIN -10.0
#define RMAX 10.0
/* Main program */
int main() {
/* Locals */
MKL_INT n = N, lda = LDA, info;
/* Local arrays */
double h = (RMAX - RMIN) / (double(N) + 1.0);
double xi;
double *w;
double *a;
w= (double*)malloc(sizeof(double) * N);
a = (double*)malloc(sizeof(double) * N*LDA);
for (int i = 0; i < N; i++) {
xi = RMIN + double(1.0+i) * h;
a[i*(N+1)] = 2.0 / h / h+xi * xi;
if (i==0) {
a[1] = -1.0 / h / h;
}
else if (i == N - 1) {
a[LDA * N-2] =- 1.0 / h / h;
}
else {
a[i *(N + 1)+1] = 2.0 / h / h + xi * xi;
a[i * (N + 1) - 1] = 2.0 / h / h + xi * xi;
}
}
/* Executable statements */
printf("LAPACKE_dsyev (row-major, high-level) Example Program Results\n");
/* Solve eigenproblem */
info = LAPACKE_dsyev(LAPACK_ROW_MAJOR, 'V', 'U', n, a, lda, w);
/* Check for convergence */
if (info > 0) {
printf("The algorithm failed to compute eigenvalues.\n");
exit(1);
}
/* Print eigenvalues */
print_matrix("Eigenvalues", 1, n, w, 1);
/* Print eigenvectors */
print_matrix("Eigenvectors (stored columnwise)", n, n, a, lda);
free(a);
free(w);
exit(0);
} /* End of LAPACKE_dsyev Example */
/* Auxiliary routine: printing a matrix */
void print_matrix(char* desc, MKL_INT m, MKL_INT n, double* a, MKL_INT lda) {
MKL_INT i, j;
printf("\n %s\n", desc);
for (i = 0; i < m; i++) {
for (j = 0; j < n; j++) printf(" %6.2f", a[i * lda + j]);
printf("\n");
}
}