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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In this master thesis by Christian Fenzl (accomplished at the university of applied sciences in
Darmstadt), an easy to use framework is implemented with additional
demos to show the main concepts of gpgpu. Furthermore, a demo implementation
is included which calculates scores on feature vectors used in a speech
recognition system (about 12 times faster than an equivalent cpu
implementation). An application with several demos using the framework including the
fully documented source code (English) and the paper itself (German) is available. The framework code is
recommended especially for gpgpu beginners to look into the OpenGL and
DirectX code which shows how gpgpu programs can be developed.
Posted: 24 May 2006 [GPGPU /Tools] # Floating-Point Computation with Just Enough Accuracy This paper by Dietz et al. from ICCS 2006
details and microbenchmarks the use of pairs of native precision values to
obtain higher accuracy results using DSP, SWAR, and GPU hardware. It
also dicusses a way to speculatively use lower precision, recomputing with
higher precisions only when accuracy constraints are not met.
( Floating-Point Computation with Just Enough Accuracy)
Posted: 24 May 2006 [GPGPU /Scientific Computing] # |
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