https://github.com/vcdevel/std-simd
std::experimental::simd for GCC [ISO/IEC TS 19570:2018]
https://github.com/vcdevel/std-simd
avx avx512 cpp17 gcc libstdcxx neon simd sse wg21
Last synced: 2 months ago
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std::experimental::simd for GCC [ISO/IEC TS 19570:2018]
- Host: GitHub
- URL: https://github.com/vcdevel/std-simd
- Owner: VcDevel
- License: other
- Created: 2019-05-07T12:32:36.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2023-03-10T15:37:36.000Z (about 2 years ago)
- Last Synced: 2025-03-28T16:05:27.719Z (2 months ago)
- Topics: avx, avx512, cpp17, gcc, libstdcxx, neon, simd, sse, wg21
- Language: C++
- Size: 3.34 MB
- Stars: 607
- Watchers: 22
- Forks: 40
- Open Issues: 27
-
Metadata Files:
- Readme: README.md
- Contributing: .github/CONTRIBUTING.md
- License: LICENSE
Awesome Lists containing this project
README
# `std::experimental::simd`
portable, zero-overhead C++ types for explicitly data-parallel programming
**Development here is going to move on to std::simd for C++26. For the TS
implementation reach for
[GCC/libstdc++](https://gcc.gnu.org/git/?p=gcc.git;a=blob;f=libstdc%2B%2B-v3/include/experimental/simd;hb=HEAD).**
`std::experimental::simd` is shipping with GCC since version 11.
This package implements ISO/IEC TS 19570:2018 Section 9 "Data-Parallel Types".
The implementation derived from https://github.com/VcDevel/Vc.
By default, the `install.sh` script places the `std::experimental::simd`
headers into the directory where the standard library of your C++ compiler
(identified via `$CXX`) resides.
It is only tested and supported with GCC trunk, even though it may work
with older GCC versions.
## Target support
* x86_64 is the main development platform and thoroughly tested. This includes
support from SSE-only up to AVX512 on Xeon Phi or Xeon CPUs.
* aarch64, arm, and ppc64le was tested and verified to work. No significant
performance evaluation was done.
* In any case, a fallback to correct execution via builtin arithmetic types is
available for all targets.
## Installation Instructions
```sh
$ ./install.sh
```
Use `--help` to learn about the available options.
## Example
### Scalar Product
Let's start from the code for calculating a 3D scalar product using builtin floats:
```cpp
using Vec3D = std::array;
float scalar_product(Vec3D a, Vec3D b) {
return a[0] * b[0] + a[1] * b[1] + a[2] * b[2];
}
```
Using `simd`, we can easily vectorize the code using the `native_simd`
type ([Compiler Explorer](https://godbolt.org/z/AXAe8K)):
```cpp
using std::experimental::native_simd;
using Vec3D = std::array, 3>;
native_simd scalar_product(Vec3D a, Vec3D b) {
return a[0] * b[0] + a[1] * b[1] + a[2] * b[2];
}
```
The above will scale to 1, 4, 8, 16, etc. scalar products calculated in parallel, depending
on the target hardware's capabilities.
For comparison, the same vectorization using Intel SSE intrinsics is more verbose, uses
prefix notation (i.e. function calls), and neither scales to AVX or AVX512, nor is it
portable to different SIMD ISAs:
```cpp
using Vec3D = std::array<__m128, 3>;
__m128 scalar_product(Vec3D a, Vec3D b) {
return _mm_add_ps(_mm_add_ps(_mm_mul_ps(a[0], b[0]), _mm_mul_ps(a[1], b[1])),
_mm_mul_ps(a[2], b[2]));
}
```
## Build Requirements
none. It's header-only.
However, to build the unit tests you will need:
* cmake >= 3.0
* GCC >= 9.1
To execute all AVX512 unit tests, you will need the Intel SDE.
## Building the tests
```sh
$ make test
```
This will create a build directory, run cmake, compile the tests, and execute the tests.
## Documentation
https://en.cppreference.com/w/cpp/experimental/simd
## Publications
* [J. Hoberock, "Working Draft, C++ Extensions for Parallelism Version 2",
2019](https://wg21.link/N4808)
* [M. Kretz, "Extending C++ for Explicit Data-Parallel Programming via SIMD
Vector Types", Goethe University Frankfurt, Dissertation,
2015.](http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/38415)
* [P. Esterie, M. Gaunard, J. Falcou and J. Lapresté, "Exploiting Multimedia Extensions
in C++: A Portable Approach," in Computing in Science & Engineering, vol. 14, no. 5,
pp. 72-77, Sept.-Oct. 2012.](https://dx.doi.org/10.1109/MCSE.2012.96)
* [M. Kretz and V. Lindenstruth, "Vc: A C++ library for explicit
vectorization", Software: Practice and Experience,
2011.](http://dx.doi.org/10.1002/spe.1149)
* [J. Falcou and J. Serot, "E.V.E., An Object Oriented SIMD Library.",
Scalable Computing: Practice and Experience, vol. 6, no. 4, pp. 72-77,
2005.](https://www.scpe.org/index.php/scpe/article/view/345/0)
## License
The `simd` headers, tests, and benchmarks are released under the terms of the
[3-clause BSD license](http://opensource.org/licenses/BSD-3-Clause).
Note that the code in libstdc++ is distributed under GPL3 with runtime library exception.