kokkos
kokkos-python
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| kokkos | kokkos-python | |
|---|---|---|
| 4 | 2 | |
| 1,723 | 24 | |
| 3.0% | - | |
| 9.8 | 3.8 | |
| 1 day ago | 3 months ago | |
| C++ | C++ | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
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.
kokkos-python
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pykokkos-base available in PyPi (numpy and cupy array interoperability)
pykokkos-base provides the ability to pass Kokkos data structures (View, DynRankView -- which are similar to NumPy's ndarray) between Python and C++ and interoperability with NumPy and CuPy arrays.
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Is there a way to get the type from type_index?
example enum #2 example usage #2.1 example usage #2.2
What are some alternatives?
RAJA - RAJA Performance Portability Layer (C++)
pykokkos - Performance portable parallel programming in Python.
timemory - Modular C++ Toolkit for Performance Analysis and Logging. Profiling API and Tools for C, C++, CUDA, Fortran, and Python. The C++ template API is essentially a framework to creating tools: it is designed to provide a unifying interface for recording various performance measurements alongside data logging and interfaces to other tools.
mdspan - Reference implementation of mdspan targeting C++23
Taskflow - A General-purpose Parallel and Heterogeneous Task Programming System
stdBLAS - Reference Implementation for stdBLAS
parallel-kd-tree - Parallel k-d tree with C++17, MPI and OpenMP
Bulk - A modern interface for implementing bulk-synchronous parallel programs.
cu - package cu provides an idiomatic interface to the CUDA Driver API.
qthreads - Lightweight locality-aware user-level threading runtime.
kokkos-kernels - Kokkos C++ Performance Portability Programming Ecosystem: Math Kernels - Provides BLAS, Sparse BLAS and Graph Kernels