Skip to content

Latest commit

 

History

History
57 lines (49 loc) · 4.83 KB

README.md

File metadata and controls

57 lines (49 loc) · 4.83 KB
Raw

Multi GPU Programming Models

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 communication
  • multi_threaded_copy Multi Threaded with OpenMP using cudaMemcpy for inter GPU communication
  • multi_threaded_copy_overlap Multi Threaded with OpenMP using cudaMemcpy for itner GPU communication with overlapping communication
  • multi_threaded_p2p Multi Threaded with OpenMP using GPUDirect P2P mappings for inter GPU communication
  • multi_threaded_p2p_opt Multi Threaded with OpenMP using GPUDirect P2P mappings for inter GPU communication with delayed norm execution
  • multi_threaded_um Multi Threaded with OpenMP relying on transparent peer mappings with Unified Memory for inter GPU communication
  • mpi Multi Process with MPI using CUDA-aware MPI for inter GPU communication
  • mpi_overlap Multi Process with MPI using CUDA-aware MPI for inter GPU communication with overlapping communication
  • nccl Multi Process with MPI and NCCL using NCCL for inter GPU communication
  • nccl_overlap Multi Process with MPI and NCCL using NCCL for inter GPU communication with overlapping communication
  • nvshmem 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 and nvshmem on DGX-1V at GTC Europe 2017 in 23031 - Multi GPU Programming Models
  • single_threaded_copy, multi_threaded_copy, multi_threaded_copy_overlap, multi_threaded_p2p, multi_threaded_p2p_opt, mpi, mpi_overlap and nvshmem 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.

Requirements

  • 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

Building

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

Run instructions

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
  • -use_hp_streams: In mpi_overlap use high priority streams to hide kernel launch latencies of boundary kernels.

The provided script bench.sh contains some examples executing all the benchmarks presented in the GTC 2019 Talk Multi GPU Programming Models.

Developers guide

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

  1. 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 and MPIX_Query_cuda_support() to be defined in mpi-ext.h, it can be skipped by setting SKIP_CUDA_AWARENESS_CHECK=1. ↩