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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).

Vec2d math implementations on ARM

Three implementations of the double-precision NEON math overloads (exp, log, sin, cos, sincos, tan) are available, selected at compile time:

  • Default (no flag): NEON port of the double-precision math functions from Agner Fog's vectorclass library. Vectorized, full f64 precision. See NeonMathDoubleVCL.hpp.
  • AVEC_USE_NEON_PD: Pommier-style NEON math from NeonMathDouble.hpp. Vectorized, but only ~f32-grade precision (~7 decimal digits) since the algorithms were originally written for single precision and ported to double without strengthening the polynomial approximations.
  • AVEC_USE_SCALAR_PD: per-lane scalar libm calls (std::sin etc.). Full f64 precision; roughly 2× the per-call cost of the vectorized variants.

The two flags are mutually exclusive. The VCL-derived default is the recommended choice; the Pommier path is kept around for cases where the lower precision is acceptable in exchange for slightly leaner codegen, and the scalar path as a portability/debug fallback.

The single-precision Vec4f math overloads always go through Pommier's NeonMathFloat.hpp — no flag involved.

Credits

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

The default Vec2d math implementation is a NEON port of the double-precision math functions (exp, log, sin, cos, sincos, tan) from Agner Fog's vectorclass library (Apache License 2.0). Algorithms (VDT / Cephes / Moshier-derived) are unchanged from VCL's vectormath_exp.h / vectormath_trig.h; only the SIMD plumbing is rewritten in NEON. See NeonMathDoubleVCL.hpp.

The single-precision NEON math overloads (Vec4f exp, log, sin, cos, sincos, tan), and the alternative double-precision Pommier-style overloads available under AVEC_USE_NEON_PD, were written by Julien Pommier and are 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.

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