verrou
sleef
verrou | sleef | |
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2 | 17 | |
44 | 594 | |
- | - | |
9.0 | 8.1 | |
7 days ago | 19 days ago | |
C | C | |
GNU General Public License v3.0 only | Boost Software License 1.0 |
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verrou
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C library for multiple-precision floating-point arithmetic with correct rounding
At the risk of just talking to myself, I'll note that a google scholar search on the [1] above led me to this phd [2] which in turn led me to two newer tools, Verrou [3] and Verificarlo [4] which involve Valgrind and Docker, respectively, though I'd have to understand what exactly is being contained by Docker for Verrou. But it makes me appreciate more the minimalist approach of Knizia et al. in [1], which does involve recompilation of modified assembly, but that's something I'm doing multiple times with student code already.
[2] https://tel.archives-ouvertes.fr/tel-03110553/document
[3] https://github.com/edf-hpc/verrou
[4] https://github.com/verificarlo/verificarlo
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.