完成可以在太湖之光上运行的主从并行复数矩阵相乘C程序

好的，我可以为您提供一个可以在太湖之光上运行的主从并行复数矩阵相乘C程序。请注意，由于我无法直接访问太湖之光，因此我不能保证该程序可以直接在太湖之光上运行，但是它是符合太湖之光架构的并行程序。下面是程序代码：

#include <stdio.h>
#include <stdlib.h>
#include <mpi.h>
#include <complex.h>

#define MASTER 0
#define TAG 0

void matmul(int n, int m, int p, int rank, int size, double complex *A, double complex *B, double complex *C);

int main(int argc, char** argv) {
    int n, m, p, rank, size;
    double complex *A, *B, *C;

    MPI_Init(&argc, &argv);
    MPI_Comm_rank(MPI_COMM_WORLD, &rank);
    MPI_Comm_size(MPI_COMM_WORLD, &size);

    if (rank == MASTER) {
        printf("Please enter the dimensions of matrices A, B and C (n, m, p): ");
        fflush(stdout);
        scanf("%d %d %d", &n, &m, &p);

        // Allocate memory for matrices
        A = (double complex*) malloc(n * m * sizeof(double complex));
        B = (double complex*) malloc(m * p * sizeof(double complex));
        C = (double complex*) malloc(n * p * sizeof(double complex));

        // Initialize matrices A and B
        for (int i = 0; i < n; i++) {
            for (int j = 0; j < m; j++) {
                A[i * m + j] = 1.0 * i + 1.0 * j * I;
            }
        }
        for (int i = 0; i < m; i++) {
            for (int j = 0; j < p; j++) {
                B[i * p + j] = 1.0 * i + 1.0 * j * I;
            }
        }
    }

    // Broadcast matrix dimensions to all processes
    MPI_Bcast(&n, 1, MPI_INT, MASTER, MPI_COMM_WORLD);
    MPI_Bcast(&m, 1, MPI_INT, MASTER, MPI_COMM_WORLD);
    MPI_Bcast(&p, 1, MPI_INT, MASTER, MPI_COMM_WORLD);

    // Allocate memory for local matrices
    int local_m = m / size;
    double complex *local_A = (double complex*) malloc(n * local_m * sizeof(double complex));
    double complex *local_B = (double complex*) malloc(local_m * p * sizeof(double complex));
    double complex *local_C = (double complex*) malloc(n * p * sizeof(double complex));

    // Scatter matrix A to all processes
    MPI_Scatter(A, n * local_m, MPI_DOUBLE_COMPLEX, local_A, n * local_m, MPI_DOUBLE_COMPLEX, MASTER, MPI_COMM_WORLD);

    // Broadcast matrix B to all processes
    MPI_Bcast(B, m * p, MPI_DOUBLE_COMPLEX, MASTER, MPI_COMM_WORLD);

    // Compute local matrix multiplication
    matmul(n, local_m, p, rank, size, local_A, local_B, local_C);

    // Gather all partial results into matrix C on master process
    MPI_Gather(local_C, n * p / size, MPI_DOUBLE_COMPLEX, C, n * p / size, MPI_DOUBLE_COMPLEX, MASTER, MPI_COMM_WORLD);

    if (rank == MASTER) {
        // Print result matrix C
        printf("Result matrix C:\n");
        for (int i = 0; i < n; i++) {
            for (int j = 0; j < p; j++) {
                printf("%f+%fi ", creal(C[i * p + j]), cimag(C[i * p + j]));
            }
            printf("\n");
        }

        // Free memory
        free(A);
        free(B);
        free(C);
    }

    free(local_A);
    free(local_B);
    free(local_C);

    MPI_Finalize();

    return 0;
}

void matmul(int n, int m, int p, int rank, int size, double complex *A, double complex *B, double complex *C) {
    // Initialize local matrix C to zero
    for (int i = 0; i < n; i++) {
        for (int j = 0; j < p; j++) {
            C[i * p + j] = 0.0 + 0.0 * I;
        }
    }

    // Compute local matrix multiplication
    for (int k = 0; k < m; k++) {
        for (int i = 0; i < n; i++) {
            for (int j = rank * p / size; j < (rank + 1) * p / size; j++) {
                C[i * p + j] += A[i * m + k] * B[k * p + j];
            }
        }
    }

    // Reduce local matrix C to global matrix C
    MPI_Allreduce(MPI_IN_PLACE, C, n * p, MPI_DOUBLE_COMPLEX, MPI_SUM, MPI_COMM_WORLD);
}

该程序使用MPI库实现了主从并行复数矩阵相乘。在程序中，主进程读取输入矩阵A和B的维度，并初始化它们的值。然后，它将矩阵A和B广播到所有进程，将矩阵A分发给每个进程，并计算本地矩阵乘积。最后，它将每个进程的本地矩阵乘积收集到矩阵C中，并在主进程打印结果。请注意，程序使用双精度复数类型double complex来表示矩阵元素。