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Brook for GPUs: Stream Computing on Graphics Hardware (2004)
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| Venue: | ACM TRANSACTIONS ON GRAPHICS |
| Citations: | 224 - 9 self |
BibTeX
@ARTICLE{Buck04brookfor,
author = {Ian Buck and Tim Foley and Daniel Horn and Jeremy Sugerman and Kayvon Fatahalian and Mike Houston and Pat Hanrahan},
title = {Brook for GPUs: Stream Computing on Graphics Hardware},
journal = {ACM TRANSACTIONS ON GRAPHICS},
year = {2004},
volume = {23},
pages = {777--786}
}
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Abstract
In this paper, we present Brook for GPUs, a system for general-purpose computation on programmable graphics hardware. Brook extends C to include simple data-parallel constructs, enabling the use of the GPU as a streaming coprocessor. We present a compiler and runtime system that abstracts and virtualizes many aspects of graphics hardware. In addition, we present an analysis of the effectiveness of the GPU as a compute engine compared to the CPU, to determine when the GPU can outperform the CPU for a particular algorithm. We evaluate our system with five applications, the SAXPY and SGEMV BLAS operators, image segmentation, FFT, and ray tracing. For these applications, we demonstrate that our Brook implementations perform comparably to hand-written GPU code and up to seven times faster than their CPU counterparts.
Keyphrases
graphic hardware many aspect cpu counterpart sgemv blas operator general-purpose computation image segmentation simple data-parallel construct ray tracing hand-written gpu code streaming coprocessor brook implementation perform runtime system compute engine particular algorithm programmable graphic hardware
