After much Googling, I have no idea what's causing this issue. Here it is:
I have a simple call to MPI_Allgather in my code which I have double, triple, and quadruple-checked to be correct (send/receive buffers are properly sized; the send/receive sizes in the call are correct), but for 'large' numbers of processes I get either a deadlock or an MPI_ERR_TRUNCATE. The communicator being used for the Allgather is split from MPI_COMM_WORLD using MPI_Comm_split. For my current testing, rank 0 goes to one communicator, and the remaining ranks go to a second communicator. For 6 total ranks or less, the Allgather works just fine. If I use 7 ranks, I get an MPI_ERR_TRUNCATE. 8 ranks, deadlock. I have verified that the communicators were split correctly (MPI_Comm_rank and MPI_Comm_size is correct on all ranks for both Comms).
I have manually verified the size of each send and receive buffer, and the maximal number of receives. My first workaround was to swap the MPI_Allgather for a for-loop of MPI_Gather's to each process. This worked for that one case, but changing the meshes given to my code (CFD grids being partitioned using METIS) brought the problem back. Now my solution, which I haven't been able to break (yet), is to replace the Allgather with an Allgatherv, which I suppose is more efficient anyways since I have a different number of pieces of data being sent from each process.
Here's the (I hope) relevant offending code in context; if I've missed something, the Allgather in question is on line 599 of this file.
// Get the number of mpiFaces on each processor (for later communication)
// 'nProgGrid' is the size of the communicator 'gridComm'
vector<int> nMpiFaces_proc(nProcGrid);
// This MPI_Allgather works just fine, every time
// int nMpiFaces is assigned on preceding lines
MPI_Allgather(&nMpiFaces,1,MPI_INT,nMpiFaces_proc.data(),1,MPI_INT,gridComm);
int maxNodesPerFace = (nDims==2) ? 2 : 4;
int maxNMpiFaces = getMax(nMpiFaces_proc);
// The matrix class is just a fancy wrapper around std::vector that
// allows for (i,j) indexing. The getSize() and getData() methods just
// call the size() and data() methods, respectively, of the underlying
// vector<int> object.
matrix<int> mpiFaceNodes_proc(nProcGrid,maxNMpiFaces*maxNodesPerFace);
// This is the MPI_Allgather which (sometimes) doesn't work.
// vector<int> mpiFaceNodes is assigned in preceding lines
MPI_Allgather(mpiFaceNodes.data(),mpiFaceNodes.size(),MPI_INT,
mpiFaceNodes_proc.getData(),maxNMpiFaces*maxNodesPerFace,
MPI_INT,gridComm);
I am currently using OpenMPI 1.6.4, g++ 4.9.2, and an AMD FX-8350 8-core processor with 16GB of RAM, running the latest updates of Elementary OS Freya 0.3 (basically Ubuntu 14.04). However, I have also had this issue on another machine using CentOS, Intel hardware, and MPICH2.
Any ideas? I have heard that it could be possible to change MPI's internal buffer size(s) to fix similar issues, but a quick try to do so (as shown in http://www.caps.ou.edu/pipermail/arpssupport/2002-May/000361.html) had no effect.
For reference, this issue is very similar to the one shown here: https://software.intel.com/en-us/forums/topic/285074, except that in my case, I have only 1 processor with 8 cores, on a single desktop computer.
UPDATE I've managed to put together a minimalist example of this failure:
#include <iostream>
#include <vector>
#include <stdlib.h>
#include <time.h>
#include "mpi.h"
using namespace std;
int main(int argc, char* argv[])
{
MPI_Init(&argc,&argv);
int rank, nproc, newID, newRank, newSize;
MPI_Comm newComm;
MPI_Comm_rank(MPI_COMM_WORLD,&rank);
MPI_Comm_size(MPI_COMM_WORLD,&nproc);
newID = rank%2;
MPI_Comm_split(MPI_COMM_WORLD,newID,rank,&newComm);
MPI_Comm_rank(newComm,&newRank);
MPI_Comm_size(newComm,&newSize);
srand(time(NULL));
// Get a different 'random' number for each rank on newComm
//int nSend = rand()%10000;
//for (int i=0; i<newRank; i++) nSend = rand()%10000;
/*! -- Found a set of #'s which fail for nproc=8: -- */
int badSizes[4] = {2695,7045,4256,8745};
int nSend = badSizes[newRank];
cout << "Comm " << newID << ", rank " << newRank << ": nSend = " << nSend << endl;
vector<int> send(nSend);
for (int i=0; i<nSend; i++)
send[i] = rand();
vector<int> nRecv(newSize);
MPI_Allgather(&nSend,1,MPI_INT,nRecv.data(),1,MPI_INT,newComm);
int maxNRecv = 0;
for (int i=0; i<newSize; i++)
maxNRecv = max(maxNRecv,nRecv[i]);
vector<int> recv(newSize*maxNRecv);
MPI_Barrier(MPI_COMM_WORLD);
cout << "rank " << rank << ": Allgather-ing data for communicator " << newID << endl;
MPI_Allgather(send.data(),nSend,MPI_INT,recv.data(),maxNRecv,MPI_INT,newComm);
cout << "rank " << rank << ": Done Allgathering-data for communicator " << newID << endl;
MPI_Finalize();
return 0;
}
The above code was compiled and run as:
mpicxx -std=c++11 mpiTest.cpp -o mpitest
mpirun -np 8 ./mpitest
with the following output on both my 16-core CentOS and my 8-core Ubuntu machines:
Comm 0, rank 0: nSend = 2695
Comm 1, rank 0: nSend = 2695
Comm 0, rank 1: nSend = 7045
Comm 1, rank 1: nSend = 7045
Comm 0, rank 2: nSend = 4256
Comm 1, rank 2: nSend = 4256
Comm 0, rank 3: nSend = 8745
Comm 1, rank 3: nSend = 8745
rank 5: Allgather-ing data for communicator 1
rank 6: Allgather-ing data for communicator 0
rank 7: Allgather-ing data for communicator 1
rank 0: Allgather-ing data for communicator 0
rank 1: Allgather-ing data for communicator 1
rank 2: Allgather-ing data for communicator 0
rank 3: Allgather-ing data for communicator 1
rank 4: Allgather-ing data for communicator 0
rank 5: Done Allgathering-data for communicator 1
rank 3: Done Allgathering-data for communicator 1
rank 4: Done Allgathering-data for communicator 0
rank 2: Done Allgathering-data for communicator 0
Note that only 2 of the ranks from each communicator exit the Allgather; this isn't what happens in my actual code (no ranks on the 'broken' communicator exit the Allgather), but the end result is the same - the code hangs until I kill it.
I'm guessing this has something to do with the differing number of sends on each process, but as far as I can tell from the MPI documentation and tutorials I've seen, this is supposed to be allowed, correct? Of course, the MPI_Allgatherv is a little more applicable, but for reasons of simplicity I have been using Allgather instead.