This project implements the well known multi GPU Jacobi solver with different multi GPU Programming Models:
single_threaded_copy
Single Threaded using cudaMemcpy for inter GPU communicationmulti_threaded_copy
Multi Threaded with OpenMP using cudaMemcpy for inter GPU communicationmulti_threaded_copy_overlap
Multi Threaded with OpenMP using cudaMemcpy for itner GPU communication with overlapping communicationmulti_threaded_p2p
Multi Threaded with OpenMP using GPUDirect P2P mappings for inter GPU communicationmulti_threaded_p2p_opt
Multi Threaded with OpenMP using GPUDirect P2P mappings for inter GPU communication with delayed norm executionmulti_threaded_um
Multi Threaded with OpenMP relying on transparent peer mappings with Unified Memory for inter GPU communicationmpi
Multi Process with MPI using CUDA-aware MPI for inter GPU communicationmpi_overlap
Multi Process with MPI using CUDA-aware MPI for inter GPU communication with overlapping communicationnccl
Multi Process with MPI and NCCL using NCCL for inter GPU communicationnccl_overlap
Multi Process with MPI and NCCL using NCCL for inter GPU communication with overlapping communicationnvshmem
Multi Process with MPI and NVSHMEM using NVSHMEM for inter GPU communication. Other approach,nvshmem_opt
, might be better for portable performance.nvshmem_opt
Multi Process with MPI and NVSHMEM using NVSHMEM for inter GPU communication with NVSHMEM extension API
Each variant is a stand alone Makefile project and most variants have been discussed in various GTC Talks, e.g.:
single_threaded_copy
,multi_threaded_copy
,multi_threaded_copy_overlap
,multi_threaded_p2p
,multi_threaded_p2p_opt
,mpi
,mpi_overlap
andnvshmem
on DGX-1V at GTC Europe 2017 in 23031 - Multi GPU Programming Modelssingle_threaded_copy
,multi_threaded_copy
,multi_threaded_copy_overlap
,multi_threaded_p2p
,multi_threaded_p2p_opt
,mpi
,mpi_overlap
andnvshmem
on DGX-2 at GTC 2019 in S9139 - Multi GPU Programming Models
Some examples in this repository are the basis for an interactive tutorial: FZJ-JSC/tutorial-multi-gpu.
- CUDA: verison 11.0 (9.2 if build with
DISABLE_CUB=1
) or later is required by all variants. - OpenMP capable compiler: Required by the Multi Threaded variants. The examples have been developed and tested with gcc.
- MPI: The "mpi" and "mpi_overlap" variants require a CUDA-aware1 implementation. For NVSHMEM and NCCL, a non CUDA-aware MPI is sufficient. The examples have been developed and tested with OpenMPI.
- NVSHMEM (version 0.4.1 or later): Required by the NVSHMEM variant.
- NCCL (version 2.8 or later): Required by the NCCL variant
Each variant come with a Makefile and can be build by simply issuing make, e.g.
multi-gpu-programming-models$ cd multi_threaded_copy
multi_threaded_copy$ make
nvcc -DHAVE_CUB -Xcompiler -fopenmp -lineinfo -DUSE_NVTX -lnvToolsExt -gencode arch=compute_70,code=sm_70 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_80,code=compute_80 -std=c++14 jacobi.cu -o jacobi
multi_threaded_copy$ ls jacobi
jacobi
All variant have the following command line options
-niter
: How many iterations to carry out (default 1000)-nccheck
: How often to check for convergence (default 1)-nx
: Size of the domain in x direction (default 16384)-ny
: Size of the domain in y direction (default 16384)-csv
: Print performance results as -csv
The provided script bench.sh
contains some examples executing all the benchmarks presented in the GTC 2019 Talk Multi GPU Programming Models.
The code applies the style guide implemented in .clang-format
file. clang-format
version 7 or later should be used to format the code prior to submitting it. E.g. with
multi-gpu-programming-models$ cd multi_threaded_copy
multi_threaded_copy$ clang-format -style=file -i jacobi.cu
Footnotes
-
A check for CUDA-aware support is done at compile and run time (see the OpenMPI FAQ for details). If your CUDA-aware MPI implementation does not support this check, which requires
MPIX_CUDA_AWARE_SUPPORT
andMPIX_Query_cuda_support()
to be defined inmpi-ext.h
, it can be skipped by settingSKIP_CUDA_AWARENESS_CHECK=1
. ↩