C++ 使用多台计算机执行失败

C++ 使用多台计算机执行失败,c++,boost,graph,mpi,qsub,C++,Boost,Graph,Mpi,Qsub,与我的工作(此处)相关,我现在正在测试一个简单代码的执行,该代码执行以下操作: 初始化boost mpi环境 将图形从文件加载到分布式邻接列表中 最后,在每台机器上对其执行2个简单操作:计算边数并计算聚类系数 代码如下: #include "Common.h" #include "GraphFileReader.h" #include "GraphNeighbors.h" #include <boost/graph/metis.hpp> #include <boost/mp

与我的工作(此处)相关,我现在正在测试一个简单代码的执行,该代码执行以下操作:

  • 初始化boost mpi环境
  • 将图形从文件加载到分布式邻接列表中
  • 最后,在每台机器上对其执行2个简单操作:计算边数并计算聚类系数
代码如下:

#include "Common.h"
#include "GraphFileReader.h"
#include "GraphNeighbors.h"
#include <boost/graph/metis.hpp>
#include <boost/mpi/environment.hpp>
#include <boost/mpi/communicator.hpp>
#include <time.h>

int main(int argc, char *argv []){

    // Start mpi enviroment
    boost::mpi::environment env(argc, argv);
    boost::mpi::communicator world;

    // Create the graph
    GraphFileReader *graphFileReader;
    undirectedAdjacencyList graph;

    if(process_id(graph.process_group()) == 0){
            // Load the graph's path
            graphFileReader = new GraphFileReader(argv[1]);
            // Read the graph file and adds the vertices and edges
            graphFileReader->loadGraph(graph);
    }

    // Wait until the process 0 has finished loading the graph
    world.barrier();
    synchronize(graph.process_group());

    GraphNeighbors graphNeighbors;

    // Now each machine should process it's own graph piece
    graphNeighbors.countEdges(graph);
    graphNeighbors.clusteringCoefficient(graph);

    // Wait for the other processes before finishing
    world.barrier();
    synchronize(graph.process_group());
    cout << "\n process: " << world.rank() <<" finishing\n" << std::endl;
我的导师和我认为这可能是因为一台机器结束了,而另一台机器仍在执行它的操作,所以我们添加了同步和屏障(我实际上不知道两者之间的区别,所以我测试了几个结果相同的组合)


如果您需要其余代码(Common.h、GraphFileReader或GraphNeighbors),我可以将其上载并在此处发布链接,以避免大量发布。

由于您正在考虑同步错误,我将简化您收到的错误消息:

图表:(boost)邻接列表。hpp:2679: boost::out_边(顶点描述符v,邻接列表&g):断言'v.owner==g.processor()'失败

等级1的退出状态:被信号6杀死

信号6由
abort()
触发,这反过来又由上述断言失败触发


我对这个图形库一无所知,但据我所知,您的处理器1似乎正在调用
out\u edges
并传递属于处理器0的顶点
v

由于您正在考虑同步错误,我将简化您收到的错误消息:

图表:(boost)邻接列表。hpp:2679: boost::out_边(顶点描述符v,邻接列表&g):断言'v.owner==g.processor()'失败

等级1的退出状态:被信号6杀死

信号6由
abort()
触发,这反过来又由上述断言失败触发


我对这个图形库一无所知,但据我所知,您的处理器1正在调用
out\u edges
并传递属于处理器0的顶点
v

非常感谢,我将尝试解决这个问题!非常感谢,我会努力解决这个问题!
graphs: /usr/include/boost/graph/distributed/adjacency_list.hpp:2679: 
std::pair<typename boost::adjacency_list<OutEdgeListS, boost::distributedS<ProcessGroup, 
InVertexListS, InDistribution>, DirectedS, VertexProperty, EdgeProperty, GraphProperty,
 EdgeListS>::out_edge_iterator, typename boost::adjacency_list<OutEdgeListS, 
boost::distributedS<ProcessGroup, InVertexListS, InDistribution>, DirectedS, 
VertexProperty, EdgeProperty, GraphProperty, EdgeListS>::out_edge_iterator> 
boost::out_edges(typename boost::adjacency_list<OutEdgeListS, 
boost::distributedS<ProcessGroup, InVertexListS, InDistribution>, DirectedS, 
VertexProperty, EdgeProperty, GraphProperty, EdgeListS>::vertex_descriptor, const 
boost::adjacency_list<OutEdgeListS, boost::distributedS<ProcessGroup, InVertexListS, 
InDistribution>, DirectedS, VertexProperty, EdgeProperty, GraphProperty, EdgeListS>&) [with
 OutEdgeListS = boost::vecS, ProcessGroup = boost::graph::distributed::mpi_process_group,
 InVertexListS = boost::vecS, InDistribution = boost::defaultS, DirectedS = 
boost::undirectedS, VertexProperty = Node, EdgeProperty = boost::no_property, GraphProperty
= boost::no_property, EdgeListS = boost::listS]: Assertion `v.owner == g.processor()' failed.

_________________________________________________________________

I'm process: 0    
I'm process: 1

Number of edges: 4
        0.37694 milliseconds
Number of edges: 2
        0.16284 milliseconds
rank 1 in job 1  compute-1-4_49342   caused collective abort of all ranks
  exit status of rank 1: killed by signal 6
_________________________________________________________________
Epilogue Args:
Job  ID:        138573.tucan
User ID:        ***
Group ID:       ***
Job Name:       mpiGraphs.job
Resource List:  5746
Queue Name:     ncpus=1,neednodes=2:ppn=2,nodes=2:ppn=2
Account String: cput=00:00:00,mem=420kb,vmem=13444kb,walltime=00:00:02
Date:           Thu Mar  1 14:28:19 CET 2012
_________________________________________________________________
I'm process: 0

Number of edges: 6
        8.46696 milliseconds
The network average clustering coefficient is: 0.53333
        0.12708 milliseconds


 process: 0 finishing