University of Illinois Urbana-Champaign

Using the High Productivity Language Chapel to Target GPGPU Architectures

Sidelnik, Albert; Chamberlain, Bradford L.; Garzaran, Maria J.; Padua, David

Content Files
techreport_chplgpu.pdf

Permalink

https://hdl.handle.net/2142/18874

Description

Title
Using the High Productivity Language Chapel to Target GPGPU Architectures
Author(s)
  • Sidelnik, Albert
  • Chamberlain, Bradford L.
  • Garzaran, Maria J.
  • Padua, David
Issue Date
2011-04-25
Keyword(s)
Chapel, HPC, GPGPU, Cuda, PGAS, Languages, Compilers
Date of Ingest
2011-04-25T20:29:09Z
Abstract
It has been widely shown that GPGPU architectures offer large performance gains compared to their traditional CPU counterparts for many applications. The downside to these architectures is that the current programming models present numerous challenges to the programmer: lower-level languages, explicit data movement, loss of portability, and challenges in performance optimization. In this paper, we present novel methods and compiler transformations that increase productivity by enabling users to easily program GPGPU architectures using the high productivity programming language Chapel. Rather than resorting to different parallel libraries or annotations for a given parallel platform, we leverage a language that has been designed from first principles to address the challenge of programming for parallelism and locality. This also has the advantage of being portable across distinct classes of parallel architectures, including desktop multicores, distributed memory clusters, large-scale shared memory, and now CPU-GPU hybrids. We present experimental results from the Parboil benchmark suite which demonstrate that codes written in Chapel achieve performance comparable to the original versions implemented in CUDA.
Type of Resource
text
Genre of Resource
Technical Report
Language
en
Permalink
http://hdl.handle.net/2142/18874
Sponsor(s)/Grant Number(s)
  • NSF CCF 0702260
  • Cray Inc. Cray-SRA-2010-01696
  • 2010-2011 Nvidia Research Fellowship

Owning Collections

Research and Tech Reports - Computer Science PRIMARY