MPI_Scatter会减慢代码的速度

各位！我写了一段代码，用MPI计算两个巨大向量的标量乘积。首先，秩为0的进程创建两个随机向量，并通过MPI_Scatter将其发送给其他进程。然后，它们计算它们的部分和，并将其发送回秩为0。主要问题是MPI_Scatter将数据发送到其他进程需要花费大量时间，因此我的程序在添加其他进程时会变慢。我用MPI_Wtime((测量了它，在某些情况下，MPI_Scatter((函数占用了80%的计算时间。我的串行代码比我尝试过的任何MPI设置都快。

以下是我在具有不同进程数的dualcore上的结果：

处理时间

序列号03275

1 03453

2 04522

4 34755

8 58645

10 89112

20 244612

40 632633

你知道如何避免这种瓶颈吗？不要介意MPI_Allgather((。。。这是家庭作业的一部分：(

int main(int argc, char* argv[])
{
srand(time(NULL));
int size, len, whoAmI, i, j, k;
int N = 10000000;
double start, elapsed_time, end;
double *Vec1, *Vec2;
MPI_Init(&argc, &argv);
start = MPI_Wtime();
MPI_Comm_size(MPI_COMM_WORLD, &size);
MPI_Comm_rank(MPI_COMM_WORLD, &whoAmI);
if(N%size != 0){
    printf("choose a number that can be divided through 10000000n");
    exit(1);
}
int chunk = N/size;
double *buf1 = malloc(chunk * sizeof(double));  // Recv_Buf for MPI_scatter
double *buf2 = malloc(chunk * sizeof(double)); 
double *gatherResult = malloc(size*(sizeof(double)));   //Recv_Buf for MPI_Allgather
double result, FinalResult = 0;
if(whoAmI == 0){
    Vec1 = malloc(N * sizeof(double));
    Vec2 = malloc(N * sizeof(double));
    random_Vector(Vec1, N);
    random_Vector(Vec2, N); 
}   
/* sends the divided array to the other processes */
MPI_Scatter(Vec1, chunk, MPI_DOUBLE, buf1, chunk, MPI_DOUBLE, 0, MPI_COMM_WORLD);
MPI_Scatter(Vec2, chunk, MPI_DOUBLE, buf2, chunk, MPI_DOUBLE, 0, MPI_COMM_WORLD);
if(whoAmI == 0){
    end = MPI_Wtime();
    elapsed_time = end - start;
    printf("Time taken %.4f secondsn", elapsed_time);
}
for(i = 0; i < chunk; i ++){
    result += buf1[i] * buf2[i];
}
printf("The sub result: #%d, %.2fn",whoAmI, result);
/* Allgather: (sendBuf, number of Elements in SendBuf, Type of Send, Number of Elements Recv, Recv Type, Comm)*/
MPI_Allgather(&result, 1 , MPI_DOUBLE, gatherResult, 1, MPI_DOUBLE , MPI_COMM_WORLD);
for(i = 0; i < size; i++){
    FinalResult += gatherResult[i]; 
}
MPI_Barrier(MPI_COMM_WORLD);
end = MPI_Wtime();
elapsed_time = end - start;
if(whoAmI == 0){
    printf("FinalResult is: %.2fn", FinalResult);
    printf("Time taken %.4f secondsn", elapsed_time);
    VecVec_Test(N, Vec1, Vec2, FinalResult);  // Test if the Result is correct
}
MPI_Barrier(MPI_COMM_WORLD);
return 0;
}

MPI_Scatter(Vec1, buf1);
MPI_Scatter(Vec2, buf2);
// Always a good idea to sync the processes before benchmarking
MPI_Barrier();
start = MPI_Wtime();
for (i = 1; i <= 1000; i++) {
   local_result = dotprod(buf1, buf2);
   MPI_Reduce(&local_result, &result, MPI_SUM);
}
end = MPI_Wtime();
printf("Time per iteration: %fn", (end - start) / 1000);