stdBLAS
kokkos-kernels
| stdBLAS | kokkos-kernels | |
|---|---|---|
| 4 | 1 | |
| 104 | 278 | |
| 8.7% | 1.8% | |
| 5.0 | 9.1 | |
| about 1 month ago | 3 days ago | |
| C++ | C++ | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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stdBLAS
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Which is the best way to work with matrices and linear algebra using c++?
You can have a look at https://github.com/kokkos/stdBLAS (it's an implementation of the proposed linear algebra extensions for future C++).
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C++23: Near The Finish Line
It has the same BSD license as Kokkos: https://github.com/kokkos/stdBLAS/blob/main/LICENSE
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Linear Algebra Library Reccomendations?
The BLAS and LAPACK have C interfaces, and they generally don't allocate memory unless you ask them. (Some BLAS implementations allocate internal storage for rearranging matrix data.) There are a few C++ BLAS wrappers; here is one of them.
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Is there an OOP-wrapper library for cublas?
The second one is stdBLAS by kokkos. It doesn't even use cuBLAS but it's a reference implementation of P1673. This paper describe what could be a blas API in the std. I would recommend trying to do something equivalent on your side.
kokkos-kernels
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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.
What are some alternatives?
mdspan - Reference implementation of mdspan targeting C++23
oneMKL - oneAPI Math Kernel Library (oneMKL) Interfaces
kokkos - Kokkos C++ Performance Portability Programming Ecosystem: The Programming Model - Parallel Execution and Memory Abstraction
plf_hive - plf::hive is a fork of plf::colony to match the current C++ standards proposal.
rocBLAS - Next generation BLAS implementation for ROCm platform
LEWG - Project planning for the C++ Library Evolution Working Group
kronmult993 - CPU and GPU implementations of kronmult.
plf_colony - An unordered C++ data container providing fast iteration/insertion/erasure while maintaining pointer/iterator validity to non-erased elements regardless of insertions/erasures. Provides higher-performance than std:: library containers for high-modification scenarios with unordered data.
cu - package cu provides an idiomatic interface to the CUDA Driver API.
papers - ISO/IEC JTC1 SC22 WG21 paper scheduling and management