使用c语言编写使用了mpi算法的PageRank，其中数据集来自于文件

下面是一个使用了MPI算法的PageRank的C语言代码，它可以从文件中读取数据集：

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

#define MAX_ITERATIONS 100
#define TOLERANCE 0.0001

int main(int argc, char **argv)
{
    int rank, size, N, i, j, count, iterations;
    double *x, *y, *local_x, *local_y, *A, *local_A, *recvbuf, sum, local_sum, start_time, end_time;

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

    if(rank == 0){
        FILE *fp = fopen("data.txt", "r");
        fscanf(fp, "%d", &N);

        x = (double*) malloc(N * sizeof(double));
        y = (double*) malloc(N * sizeof(double));
        A = (double*) malloc(N * N * sizeof(double));

        for(i = 0; i < N; i++){
            fscanf(fp, "%lf", &x[i]);
            y[i] = 1.0 / N;
            for(j = 0; j < N; j++){
                fscanf(fp, "%lf", &A[i*N+j]);
            }
        }

        fclose(fp);
    }

    MPI_Bcast(&N, 1, MPI_INT, 0, MPI_COMM_WORLD);

    count = N / size;
    local_x = (double*) malloc(count * sizeof(double));
    local_y = (double*) malloc(count * sizeof(double));
    local_A = (double*) malloc(count * N * sizeof(double));
    recvbuf = (double*) malloc(N * sizeof(double));

    MPI_Scatter(x, count, MPI_DOUBLE, local_x, count, MPI_DOUBLE, 0, MPI_COMM_WORLD);
    MPI_Scatter(y, count, MPI_DOUBLE, local_y, count, MPI_DOUBLE, 0, MPI_COMM_WORLD);
    MPI_Scatter(A, count*N, MPI_DOUBLE, local_A, count*N, MPI_DOUBLE, 0, MPI_COMM_WORLD);

    start_time = MPI_Wtime();
    iterations = 0;
    do{
        iterations++;
        local_sum = 0.0;

        for(i = 0; i < count; i++){
            sum = 0.0;
            for(j = 0; j < N; j++){
                sum += local_A[i*N+j] * local_y[j];
            }
            local_x[i] = sum;
            local_sum += sum;
        }

        MPI_Allgather(local_x, count, MPI_DOUBLE, recvbuf, count, MPI_DOUBLE, MPI_COMM_WORLD);
        for(i = 0; i < N; i++){
            local_y[i] = recvbuf[i];
        }

        MPI_Allreduce(&local_sum, &sum, 1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD);
        for(i = 0; i < count; i++){
            local_x[i] = local_x[i] / sum;
        }

        MPI_Allgather(local_x, count, MPI_DOUBLE, recvbuf, count, MPI_DOUBLE, MPI_COMM_WORLD);
        for(i = 0; i < N; i++){
            local_y[i] = recvbuf[i];
        }

        local_sum = 0.0;
        for(i = 0; i < count; i++){
            local_sum += (local_x[i] - local_y[i]) * (local_x[i] - local_y[i]);
        }

        MPI_Allreduce(&local_sum, &sum, 1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD);

    }while(iterations < MAX_ITERATIONS && sum > TOLERANCE);

    end_time = MPI_Wtime();

    if(rank == 0){
        printf("Final PageRank values:\n");
        for(i = 0; i < N; i++){
            printf("%d: %lf\n", i, y[i]);
        }
        printf("Time taken: %lf seconds\n", end_time - start_time);
    }

    MPI_Finalize();
    return 0;
}

该代码使用了scatter、allgather、allreduce等MPI函数来实现PageRank算法。在运行该代码之前，需要将数据集存储在名为"data.txt"的文件中，其中第一行为数据集的大小N，接下来的N行为x向量和N*N的矩阵A。

注意，该代码的运行需要MPI运行环境的支持。可以使用mpicc编译器来编译该代码：

mpicc -o pagerank pagerank.c

然后使用mpirun命令来运行：

mpirun -n 4 ./pagerank

其中"-n 4"表示使用4个进程来运行该程序。