SIMD parallelism has become an increasingly important mechanism for delivering performance in modern CPUs, due its power efficiency and relatively low cost in die area compared to other forms of parallelism. Unfortunately, languages and compilers for CPUs have not kept up with the hardware's capabilities. Existing CPU parallel programming models focus primarily on multi-core parallelism, neglecting the substantial computational capabilities that are available in CPU SIMD vector units. GPU-oriented languages like OpenCL support SIMD but lack capabilities needed to achieve maximum efficiency on CPUs and suffer from GPU-driven constraints that impair ease of use on CPUs.
We have developed a compiler, the Intel(R) SPMD Program Compiler
(ispc), that delivers very high performance on CPUs thanks to effective
use of both multiple processor cores and SIMD vector units. ispc draws
from GPU programming languages, which have shown that for many
applications the easiest way to program SIMD units is to use a
single-program, multiple-data (SPMD) model, with each instance of the
program mapped to one SIMD lane. We discuss language features that
make ispc easy to adopt and use productively with existing software
systems and show that ispc delivers up to 35x speedups on a 4-core
system and up to 240x speedups on a 40-core system for complex
workloads (compared to serial C++ code).
Paper -- final version (PDF, 374 KB)
@inproceedings{pharr12,
author = {Matt Pharr and William R. Mark},
title = {{ispc:} A {SPMD} Compiler for High-Performance CPU Programming},
booktitle = {Innovative Parallel Computing Conf.},
month = {May},
year = {2012},
}