Programming Models on Polaris
The software environment on Polaris supports several parallel programming models targeting the CPUs and GPUs.
CPU Parallel Programming Models
The Cray compiler wrappers
ftn are recommended for MPI applications as they provide the needed include paths and libraries for each programming environment. A summary of available CPU parallel programming models and relevant compiler flags is shown below. Users are encouraged to review the corresponding man pages and documentation.
Higher-level programming models such as Kokkos and Raja may also be used for CPU programming.
GPU Programming Models
A summary of available GPU programming models and relevant compiler flags is shown below for compilers that generate offloadable code. Users are encouraged to review the corresponding man pages and documentation.
|SYCL||--||--||--||-fsycl -fsycl-targets=nvptx64-nvidia-cuda -Xsycl-target-backend '--cuda-gpu-arch=sm_80'|
llvm-sycl modules are provided by ALCF to complement the compilers provided by the Cray PE on Polaris.
Higher-level programming models such as Kokkos and Raja may also be used for GPU programming.
OpenCL is supported, but does not require specific compiler flags per-se as the offloaded kernels are just-in-time compiled. Abstraction programming models, such as Kokkos, can be built on top of some of these programming models (see below).
A HIP compiler supporting the A100 GPUs is still to be installed on Polaris.
Mapping Programming Models to Polaris Modules
The table below offers some suggestions for how to get started setting up your environment on Polaris depending on the programming language and model. Note, mixed C/C++ and Fortran applications should choose the programming environment for the Fortran compiler because of mpi.mod and similar incompatibilities between Fortran-generated files from different compilers. Several simple examples for testing the software environment on Polaris for different programming models are available in the ALCF GettingStart repo.
Note, users are encouraged to use
PrgEnv-nvhpc instead of
PrgEnv-nvidia as the latter will soon be deprecated in Cray's PE. They are otherwise identical pointing to compilers from the same NVIDIA SDK version.
|Programming Language||GPU Programming Model||Likely used Modules/Compilers||Notes|
|C/C++||CUDA||PrgEnv-nvhpc, PrgEnv-gnu, llvm||NVIDIA (nvcc, nvc, nvc++) and clang compilers do GPU code generation|
|C/C++||HIP||N/A||need to install with support for A100|
|C/C++||Kokkos||See CUDA||HIP, OpenMP, and SYCL/DPC++ also candidates|
|C/C++||OpenCL||PrgEnv-nvhpc, PrgEnv-gnu, llvm||JIT GPU code generation|
|C/C++||RAJA||See CUDA||HIP, OpenMP, and SYCL/DPC++ also candidates|
|Fortran||CUDA||PrgEnv-nvhpc||NVIDIA compiler (nvfortran) does GPU code generation;
|Fortran||HIP||N/A||need to install with support for A100|
|Fortran||OpenCL||PrgEnv-nvhpc, PrgEnv-gnu||JIT GPU code generation|