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CUDA-aware MPI multi-GPU test
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| using MPI | |
| using CUDA | |
| MPI.Init() | |
| comm = MPI.COMM_WORLD | |
| rank = MPI.Comm_rank(comm) | |
| # select device | |
| comm_l = MPI.Comm_split_type(comm, MPI.COMM_TYPE_SHARED, rank) | |
| rank_l = MPI.Comm_rank(comm_l) | |
| gpu_id = CUDA.device!(rank_l) | |
| # select device | |
| size = MPI.Comm_size(comm) | |
| dst = mod(rank+1, size) | |
| src = mod(rank-1, size) | |
| println("rank=$rank rank_loc=$rank_l (gpu_id=$gpu_id), size=$size, dst=$dst, src=$src") | |
| N = 4 | |
| send_mesg = CuArray{Float64}(undef, N) | |
| recv_mesg = CuArray{Float64}(undef, N) | |
| fill!(send_mesg, Float64(rank)) | |
| CUDA.synchronize() | |
| rank==0 && println("start sending...") | |
| MPI.Sendrecv!(send_mesg, dst, 0, recv_mesg, src, 0, comm) | |
| println("recv_mesg on proc $rank_l: $recv_mesg") | |
| rank==0 && println("done.") |
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Hi, it could be you're MPI has no CUDA-aware support. For CUDA-aware MPI to work, you should use system MPI that was linked against local CUDA install during compilation. If you are using system MPI that is supposed to be CUDA-aware, you can check it's functionality by typing
MPI.has_cuda()(see here).