unevens / avec

A little library for using SIMD instructions for x86 and ARM, wrapping Agner Fog's vectorclass for x86 and filling some of its functionality for ARM, and providing containers for aligned memory with views and interleaving/deinterleaving.

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avec is a little library for using SIMD instructions on both x86 and ARM.

It features containers for aligned memory, with views, allocators and interleaving/deinterleaving functionality.

The API is designed to work seamlessly with Agner Fog's vectorclass, which is included as a submodule.

Since vectorclass only supports x86, avec reimplements a subset of its functionality for ARM using NEON. See the section ARM support for details.

Containers and views

In vectorclass each SIMD type has its own class: Vec4f for __m128, Vec8f for __m256, Vec4d for __m256d and so on.

In avec, the template classes VecBuffer<Vec> and VecView<Vec> are used to manage blocks of aligned memory and convert it to and from the SIMD classes of vectorclass.

Interleaving

The template class InterleavedBuffer<Scalar> (where Scalar can be either float or double) is used to interleave a buffer of any number of audio channels into a set of VecBuffer<Vec8f>, VecBuffer<Vec4f> and VecBuffer<Vec2f> (when Scalar is float), or of VecBuffer<Vec8d>, VecBuffer<Vec4d> and VecBuffer<Vec2d> (when Scalar is double).

Only the VecBuffers whose underlying vectorclass type is supported by the hardware will be used, in order to easily abstract over the many SIMD instruction sets.

ARM support

On ARM, Vec4f and Vec2d are implemented for float32x4_t and float64x2_t, with most of their member functions, all of their operators overloaded, and some math function overloads (exp, log, sin, cos, sincos, tan).

Credits

avec includes code from Boost.Align by Joseph Fernandes, without depending on the whole Boost library. See the file BoostAlign.hpp.

The implementation of exp, log, sin, cos, sincos, for ARM NEON was written by Julien Pommier, and it is available at http://gruntthepeon.free.fr/ssemath/neon_mathfun.html.

Documentation

The documentation, available at https://unevens.github.io/avec/, can be generated with Doxygen running

$ doxygen doxyfile.txt

About

A little library for using SIMD instructions for x86 and ARM, wrapping Agner Fog's vectorclass for x86 and filling some of its functionality for ARM, and providing containers for aligned memory with views and interleaving/deinterleaving.

License:Apache License 2.0


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