kokkos
RAJA
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kokkos | RAJA | |
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4 | 2 | |
1,723 | 437 | |
3.0% | 2.1% | |
9.8 | 9.7 | |
1 day ago | 5 days ago | |
C++ | C++ | |
GNU General Public License v3.0 or later | BSD 3-clause "New" or "Revised" License |
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kokkos
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Requesting suggestions for languages, libraries, and architectures for parallel (and sometimes non parallel) numerical and scientific computations
I’m a novice user of Kokkos. Write code once for openmp, CUDA, and other parallel execution backends. It was designed with scientific computing applications in mind. Some numerics tools are implemented in “Kokkos kernels”, most of the BLAS operations are included iirc.
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My first non-trivial project in C++ and MPI/OpenMP
I would suggest using a C++ abstraction around thread parallelism. This will make your code easier to read and more concise, and will also make it easier to switch between different thread-parallel programming models. Kokkos is a lovely example of such an abstraction, but there are others. Modern C++ even has thread-parallel standard algorithms. Bryce Adelstein Lelbach's CppCon 2021 talk describes these.
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Is there an OOP-wrapper library for cublas?
It’s a work in progress, but Kokkos and the associated Kokkos Kernels are probably the closest thing to what you’re asking for.
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pykokkos-base available in PyPi (numpy and cupy array interoperability)
Kokkos implements a programming model in C++ for writing performance portable applications targeting all major HPC platforms. It provides abstractions for both parallel execution of code and data management with a variety of backends including, but not limited to: CUDA, HIP, OpenMP, HPX, and Pthreads, with backends for OpenMPTarget and SYCL currently under development.
RAJA
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Cuda application question
Since the ability to use C++ parallel algorithms on the GPU is a relatively new thing, some applications have used other C++ abstraction libraries instead, such as Kokkos (https://kokkos.org/) and RAJA (https://github.com/LLNL/RAJA). These both have multiple backends that support GPUs and CPUs without needing to change your application code.
- Kokkos C++ Performance Portability Programming EcoSystem
What are some alternatives?
pykokkos - Performance portable parallel programming in Python.
mfem - Lightweight, general, scalable C++ library for finite element methods
mdspan - Reference implementation of mdspan targeting C++23
cuda-samples - Samples for CUDA Developers which demonstrates features in CUDA Toolkit
Taskflow - A General-purpose Parallel and Heterogeneous Task Programming System
CHAI - Copy-hiding array abstraction to automatically migrate data between memory spaces
kokkos-python - Python bindings for data interoperability with Kokkos (View, DynRankView)
Umpire - An application-focused API for memory management on NUMA & GPU architectures
stdBLAS - Reference Implementation for stdBLAS
Vc - SIMD Vector Classes for C++
parallel-kd-tree - Parallel k-d tree with C++17, MPI and OpenMP
Bulk - A modern interface for implementing bulk-synchronous parallel programs.