GPGPU |
General-Purpose Computation Using Graphics Hardware
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IntroductionGPGPU stands for General-Purpose computation on GPUs. With the increasing programmability of commodity graphics processing units (GPUs), these chips are capable of performing more than the specific graphics computations for which they were designed. They are now capable coprocessors, and their high speed makes them useful for a variety of applications. The goal of this page is to catalog the current and historical use of GPUs for general-purpose computation.
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Brook for GPUs: Stream Computing on Graphics Hardware Abstract
This SIGGRAPH 2004 paper by Buck et al. presents 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. The paper presents a compiler and runtime system that abstracts and virtualizes many aspects of graphics hardware. In addition, the paper provides 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. The paper evaluates the system with five applications, the SAXPY and SGEMV BLAS operators, image segmentation, FFT, and ray tracing. For these applications, the Brook implementations perform comparably to hand-written GPU code and up to seven times faster than their CPU counterparts. (Brook for GPUs: Stream Computing on Graphics Hardware. Ian Buck, Tim Foley, Daniel Horn, Jeremy Sugerman, Kayvon Fatahalian, Mike Houston, and Pat Hanrahan. To appear at SIGGRAPH 2004.)
Posted: 23 May 2004 [GPGPU /High-Level Languages] # |
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