CppCon 2016

SIMD extensions have been a feature of choice for processor manufacturers for a couple of decades. Designed to exploit data parallelism in applications at the instruction level, these extensions still require a high level of expertise or the use of potentially fragile compiler support or vendor-specific libraries. While a large fraction of their theoretical accelerations can be obtained using such tools, exploiting such hardware becomes tedious as soon as application portability across hardware is required.

Accessing such capabilities directly from C++ code could be a major improvements in a lot of use cases. Different take on this has been proposed either by the community or as an actual standard proposal. Solutions include pragma based annotations, standard algorithms policies, full blown compiler support and libraries.
In this talk we will present one such solution - the Boost.SIMD library (currently being proposed as such) which takes a library approach to this issues.

We will go over the basic notion required to grasp SIMD programming in general. Then, we'll discuss the different existing approaches. We will describe Boost.SIMD API and API design to demonstrate how it solves issues raised by the actual idiomatic way of writting SIMD enabled code. Design issues like standard algorithm integration, memory handling and how to fill the gaps in SIMD instructions sets will be discussed. Finally, we show its performances with respect to a subset of well known benchmarks.