kokkos
mdspan
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kokkos | mdspan | |
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4 | 6 | |
1,723 | 373 | |
3.0% | 4.3% | |
9.8 | 8.7 | |
1 day ago | 12 days 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.
mdspan
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July 2022 ISO C++ committee virtual meeting report
Why not use https://github.com/kokkos/mdspan though ?
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C++ for scientific programming?
It can be the base of whatever *you* write via bindings generators like pybind11. In that sense, the answer to your question is "however you like". For actual simulation code, you'll see a lot more legacy Fortran and C. That said, with things like mdspan maybe being standardized (proposal), efforts towards a standard linear algebra library, and the existence of ubiquitous HPC frameworks already having been written in C++, I would say it's only a matter of time before C++ accounts for an even bigger share of all HPC code.
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[D] Deep Learning Framework for C++.
I'm aware of only two relevant projects myself, I don't know much, came to reddit kind of by chance. One of the multi-dimensional array libraries proposed for potential standardisation, and a gnu machine learning library that was discontinued which could be worked off of. There's probably a lot more out there, but don't get distracted from making something awesome :)
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Array template implementation
As u/IyeOnline already made the important points about VLAs and std::vector, I would just add that you may find std::mdspan to be a helpful data structure. You can allocate 1d memory and give it a 2d shape of k with nice 2d indexing, eg auto& elem = mymdspan(row, col);.
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C++23: Near The Finish Line
Kokkos mdspan
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Is there an OOP-wrapper library for cublas?
The good thing here is that it heavily relies on mdpsan that is a multidimensional view that handle shape and strides. And kokkos provide a C++14 compatible implementation with a complete CUDA support.
What are some alternatives?
RAJA - RAJA Performance Portability Layer (C++)
stdBLAS - Reference Implementation for stdBLAS
pykokkos - Performance portable parallel programming in Python.
circle - The compiler is available for download. Get it!
Taskflow - A General-purpose Parallel and Heterogeneous Task Programming System
kokkos-kernels - Kokkos C++ Performance Portability Programming Ecosystem: Math Kernels - Provides BLAS, Sparse BLAS and Graph Kernels
kokkos-python - Python bindings for data interoperability with Kokkos (View, DynRankView)
plf_hive - plf::hive is a fork of plf::colony to match the current C++ standards proposal.
deepdetect - Deep Learning API and Server in C++14 support for Caffe, PyTorch,TensorRT, Dlib, NCNN, Tensorflow, XGBoost and TSNE
parallel-kd-tree - Parallel k-d tree with C++17, MPI and OpenMP
marian - Fast Neural Machine Translation in C++