safe_numerics
Vc
safe_numerics | Vc | |
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- | 6 | |
205 | 1,420 | |
-0.5% | 0.9% | |
0.0 | 6.1 | |
17 days ago | 3 months ago | |
C++ | C++ | |
Boost Software License 1.0 | BSD 3-clause "New" or "Revised" License |
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safe_numerics
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Tracking mentions began in Dec 2020.
Vc
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The Bitter Truth: Python 3.11 vs Cython vs C++ Performance for Simulations
Most high-performance math libraries perform a lot of vectorization (Eigen, etc) under the hood. And you've got stuff like Klein, Vc (which is reminiscent of std::valarray), etc. Then there's OpenMP's #pragma omp simd (assuming version 4.0 or greater).
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John "God" Carmack: C++ with a C flavor is still the best (also: Python performance "keeps hitting me in the face")
I personally like the ideas in Parallelism v2 TS, which is available in for libstdc++ 11 onwards. The reference implementation is a library named Vc (afaik Vc is the most popular SIMD library for C++), and this has also been implemented in recent versions of HPX.
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SPO600 project part 2
First of all about our project, I previously decided to work with VC library.https://github.com/VcDevel/Vc
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SPO600 project part 1
I've decided to switch to something better, and after a few hours of searching, I found this repository: NSIMD https://github.com/agenium-scale/nsimd FastDifferentialCoding https://github.com/lemire/FastDifferentialCoding VS https://github.com/VcDevel/Vc XSIMD https://github.com/xtensor-stack/xsimd
- Vc 1.4.2 released: portable SIMD programming for C++
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All C++20 core language features with examples
> - Waiting for Cross-Platform standardized SIMD vector datatypes
which language has standardized SIMD vector datatypes ? most languages don't even have any ability to express SIMD while in C++ I can just use Vc (https://github.com/VcDevel/Vc), nsimd (https://github.com/agenium-scale/nsimd) or one of the other ton of alternatives, and have stuff that JustWorksTM on more architectures than most languages even support
- Using nonstandard extensions, libraries or home-baked solutions to run computations in parallel on many cores or on different processors than the CPU
what are the other native languages with a standardized memory model for atomics ? and, what's the problem with using libraries ? it's not like you're going to use C# or Java's built-in threadpools if you are doing any serious work, no ? Do they even have something as easy to use as https://github.com/taskflow/taskflow ?
- Debugging cross-platform code using couts, cerrs and printfs
because people never use console.log in JS or System.println in C# maybe ?
- Forced to use boost for even quite elementary operations on std::strings.
can you point to non-trivial java projects that do not use Apache Commons ? Also, the boost string algorithms are header-only so you will end up with exactly the same binaries that if it was in some std::string_algorithms namespace:
https://gcc.godbolt.org/z/43vKadbde
What are some alternatives?
ExprTK - C++ Mathematical Expression Parsing And Evaluation Library https://www.partow.net/programming/exprtk/index.html
highway - Performance-portable, length-agnostic SIMD with runtime dispatch
muparser - muparser is a fast math parser library for C/C++ with (optional) OpenMP support.
xsimd - C++ wrappers for SIMD intrinsics and parallelized, optimized mathematical functions (SSE, AVX, AVX512, NEON, SVE))
MIRACL - MIRACL Cryptographic SDK: Multiprecision Integer and Rational Arithmetic Cryptographic Library is a C software library that is widely regarded by developers as the gold standard open source SDK for elliptic curve cryptography (ECC).
Eigen
QuantLib - The QuantLib C++ library
blaze
CGal - The public CGAL repository, see the README below
OpenBLAS - OpenBLAS is an optimized BLAS library based on GotoBLAS2 1.13 BSD version.
GLM - OpenGL Mathematics (GLM)