An Analysis of GPU Parallel Computing

Author

Park, Song Jun

Author_Institution

US Army Res. Lab. (ARL), Aberdeen Proving Ground, MD, USA

fYear

2009

fDate

15-18 June 2009

Firstpage

365

Lastpage

369

Abstract

Parallel systems are becoming ubiquitous in the world of computing as evidenced by multi-core processors, heterogeneous Cell broadband engine, and highly parallel graphics processing units (GPUs). All parallel systems share a requirement that parallel programming is necessary to leverage multiple cores. As a result of this trend, multi-core CPUs are no longer a clear winner due to its peaked clock frequency and programming effort involved in parallelizing code for multi-core architecture. Given such drawbacks, dataparallel applications might benefit from GPU assisted computing. GPUs are the most popular and inexpensive accelerators. To evaluate GPU-based computing, a floating-point intensive algorithm for a radar imaging application is chosen for analysis. The paper attempts to present a fair performance comparison of CPU and GPU implementations.

Keywords

computer graphic equipment; coprocessors; multiprocessing systems; parallel architectures; parallel programming; radar computing; radar imaging; GPU parallel computing; floating-point intensive algorithm; graphics processing units; heterogeneous Cell broadband engine; multicore architecture; multicore processors; parallel programming; parallel systems; radar imaging application; Graphics processing unit; Imaging; Instruction sets; Programming; Radar imaging;

fLanguage

English

Publisher

ieee

Conference_Titel

DoD High Performance Computing Modernization Program Users Group Conference (HPCMP-UGC), 2009

Conference_Location

San Diego, CA

Print_ISBN

978-1-4244-5768-7

Electronic_ISBN

978-1-4244-5769-4

Type

conf

DOI

10.1109/HPCMP-UGC.2009.59

Filename

5729490