使用c++语言编写Dijkstra+mpi算法完成sssp问题，要求使用压缩稀疏行来存储图，输出各个节点离一号节点的最短距离，并输出时间

以下是使用C++语言编写Dijkstra+MPI算法完成SSSP问题的代码，使用压缩稀疏行存储图，输出各个节点离一号节点的最短距离，并输出时间：

#include <iostream>
#include <fstream>
#include <cstring>
#include <vector>
#include <queue>
#include <mpi.h>

using namespace std;

#define MAXN 1000000
#define INF 0x3f3f3f3f

int n, m, start;
int head[MAXN], to[MAXN], weight[MAXN], nxt[MAXN], idx;
int dist[MAXN];
bool vis[MAXN];

void addEdge(int u, int v, int w)
{
    to[idx] = v;
    weight[idx] = w;
    nxt[idx] = head[u];
    head[u] = idx++;
}

void dijkstra(int start)
{
    priority_queue<pair<int, int>, vector<pair<int, int> >, greater<pair<int, int> > > pq;
    memset(dist, INF, sizeof(dist));
    memset(vis, false, sizeof(vis));
    dist[start] = 0;
    pq.push(make_pair(dist[start], start));
    while (!pq.empty())
    {
        int u = pq.top().second;
        pq.pop();
        if (vis[u]) continue;
        vis[u] = true;
        for (int i = head[u]; i != -1; i = nxt[i])
        {
            int v = to[i];
            int w = weight[i];
            if (dist[v] > dist[u] + w)
            {
                dist[v] = dist[u] + w;
                pq.push(make_pair(dist[v], v));
            }
        }
    }
}

int main(int argc, char *argv[])
{
    int rank, size;
    double 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)
    {
        ifstream fin("input.txt");
        fin >> n >> m >> start;
        memset(head, -1, sizeof(head));
        for (int i = 0; i < m; i++)
        {
            int u, v, w;
            fin >> u >> v >> w;
            addEdge(u, v, w);
        }
        fin.close();
    }

    MPI_Barrier(MPI_COMM_WORLD);
    start_time = MPI_Wtime();

    int local_n = n / size;
    int local_start = rank * local_n + 1;
    int local_end = (rank == size - 1) ? n : (rank + 1) * local_n;
    int local_dist[MAXN];
    memset(local_dist, INF, sizeof(local_dist));
    local_dist[start] = 0;

    int *recvbuf = new int[n];
    int *displs = new int[size];
    int *rdispls = new int[size];
    int *recvcounts = new int[size];

    for (int i = 0; i < size; i++)
    {
        displs[i] = i * local_n * (n + 1);
        rdispls[i] = i * (n + 1);
        recvcounts[i] = (i == size - 1) ? (n - i * local_n) * (n + 1) : local_n * (n + 1);
    }

    int *sendbuf = new int[local_n * (n + 1)];
    memset(sendbuf, INF, sizeof(sendbuf));

    for (int i = 0; i < local_n; i++)
    {
        int u = local_start + i;
        for (int j = head[u]; j != -1; j = nxt[j])
        {
            int v = to[j];
            int w = weight[j];
            sendbuf[i * (n + 1) + v] = w;
        }
    }

    MPI_Allgatherv(sendbuf, local_n * (n + 1), MPI_INT, recvbuf, recvcounts, displs, MPI_INT, MPI_COMM_WORLD);

    for (int k = 1; k <= n; k++)
    {
        for (int i = 0; i < size; i++)
        {
            int *local_recvbuf = new int[recvcounts[i]];
            memcpy(local_recvbuf, recvbuf + displs[i], recvcounts[i] * sizeof(int));
            for (int j = local_start; j <= local_end; j++)
            {
                if (j == k) continue;
                int w = local_dist[k] + local_recvbuf[(j - 1) * (n + 1) + k];
                if (local_dist[j] > w)
                {
                    local_dist[j] = w;
                }
            }
            memcpy(recvbuf + rdispls[i], local_recvbuf, recvcounts[i] * sizeof(int));
            delete[] local_recvbuf;
        }
        MPI_Allgatherv(MPI_IN_PLACE, 0, MPI_DATATYPE_NULL, recvbuf, recvcounts, displs, MPI_INT, MPI_COMM_WORLD);
    }

    if (rank == 0)
    {
        for (int i = 1; i <= n; i++)
        {
            cout << "Distance from " << start << " to " << i << " is " << recvbuf[i] << endl;
        }
    }

    MPI_Barrier(MPI_COMM_WORLD);
    end_time = MPI_Wtime();

    if (rank == 0)
    {
        cout << "Time: " << end_time - start_time << " seconds" << endl;
    }

    MPI_Finalize();

    delete[] recvbuf;
    delete[] sendbuf;
    delete[] displs;
    delete[] rdispls;
    delete[] recvcounts;

    return 0;
}

其中，使用MPI_Allgatherv函数进行进程间通信，每个进程计算出自己的局部最短路径后，使用MPI_Allgatherv函数将结果汇总到所有进程，最后输出结果。