nsimd
sleef
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nsimd | sleef | |
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2 | 17 | |
315 | 589 | |
1.6% | - | |
0.0 | 8.1 | |
over 2 years ago | 3 days ago | |
C | C | |
MIT License | Boost Software License 1.0 |
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nsimd
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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
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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
sleef
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The Case of the Missing SIMD Code
I'm the main author of Highway, so I have some opinions :D Number of operations/platforms supported are important criteria.
A hopefully unbiased commentary:
Simde allows you to take existing nonportable intrinsics and get them to run on another platform. This is useful when you have a bunch of existing code and tight deadlines. The downside is less than optimal performance - a portable abstraction can be more efficient than forcing one platform to exactly match the semantics of another. Although a ton of effort has gone into Simde, sometimes it also resorts to autovectorization which may or may not work.
Eigen and SLEEF are mostly math-focused projects that also have a portability layer. SLEEF is designed for C and thus has type suffixes which are rather verbose, see https://github.com/shibatch/sleef/blob/master/src/libm/sleef... But it offers a complete (more so than Highway's) libm.
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Does anyone have any interest in my deep-learning framework?
But the other part about SIMD: I'm unsure if mgl-mat uses SIMD for transcendental functions or even for something like element-wise multiplication and division*. SIMD easily provides a speed-boost of 4-8 times which numpy uses. Libraries like sleef have been put to use by many.
- `constexpr` what?
- Advice on porting glibc trig functions to SIMD
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SIMD intrinsics and the possibility of a standard library solution
Highway and Agner's VectorClass also have math functions. And SLEEF should definitely be mentioned.
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Portable SIMD library
"SIMD Library for Evaluating Elementary Functions, vectorized libm and DFT" - https://github.com/shibatch/sleef
- SIMD Library for Evaluating Elementary Functions, Vectorized Libm and DFT
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C library for multiple-precision floating-point arithmetic with correct rounding
Not mentioned in the list of users is SLEEF (https://github.com/shibatch/sleef), which provides fast approximations for various elementary functions. (It generates coefficients for the approximations with mpfr)
SLEEF itself is used by PyTorch.
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How to speed up array writes?
If you are looking at floats, there's https://sleef.org
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Benchmarking sine approximations and interpolators.
It would be interesting to see SLEEF added in the benchmarks.
What are some alternatives?
simde - Implementations of SIMD instruction sets for systems which don't natively support them.
yenten-arm-miner-yespowerr16 - ARM 64 CPU miner for Yespower variant algorithms
std-simd - std::experimental::simd for GCC [ISO/IEC TS 19570:2018]
sb-simd - A convenient SIMD interface for SBCL.
Vc - SIMD Vector Classes for C++
vector-libm
highway - Performance-portable, length-agnostic SIMD with runtime dispatch
crlibm - A mirror of the CRLibm project from INRIA Forge
highway - Highway - A Modern Javascript Transitions Manager
xbyak_aarch64
xsimd - C++ wrappers for SIMD intrinsics and parallelized, optimized mathematical functions (SSE, AVX, AVX512, NEON, SVE))
rlibm-32 - RLibm for 32-bit representations (float and posit32)