sleef
cl-waffe
| sleef | cl-waffe | |
|---|---|---|
| 17 | 3 | |
| 590 | 45 | |
| - | - | |
| 8.1 | 10.0 | |
| 9 days ago | 8 months ago | |
| C | Common Lisp | |
| Boost Software License 1.0 | MIT License |
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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.
cl-waffe
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Does anyone have any interest in my deep-learning framework?
cl-waffe performs basic mathematical operations (e.g.: sin/cos, exp...) via mgl-mat, and I pay a lot of attention to the overhead between cl-waffe and mgl-mat in the benchmarks. codes are here
What are some alternatives?
nsimd - Agenium Scale vectorization library for CPUs and GPUs
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tensorflow - An Open Source Machine Learning Framework for Everyone
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crlibm - A mirror of the CRLibm project from INRIA Forge
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TH - Deep Learning Library for Common Lisp.