SCHEDULE: NOV 10-16, 2007

High Performance Computing on GPUs with CUDA

Session: S05

Event Type: Tutorial

Time: 8:30am - 5:00pm

Presenter(s): Massimiliano Fatica, David P. Luebke, Ian A. Buck, John D. Owens, Mark J. Harris, John E. Stone, James C. Phillips, Bernard Deschizeaux

Location: A3

Abstract:
NVIDIA's Compute Unified Driver Architecture (CUDA) platform is a co-designed hardware and software stack that expands the GPU beyond a graphics processor to a general-purpose parallel coprocessor with tremendous computational horsepower, and makes that horsepower accessible in a familiar environment - the C programming language. Scientists throughout industry and academia are already using CUDA to achieve dramatic speedups on production codes.

In this tutorial NVIDIA engineers will partner with academic and industrial researchers to present CUDA and discuss its advanced use for science and engineering domains. The morning session will introduce CUDA programming and the execution and memory models at its heart, motivate the use of CUDA with many brief examples from different HPC domains, and discuss fundamental algorithmic building blocks in CUDA. The afternoon will discuss advanced issues such as optimization and 'tips & tricks', and include real-world case studies from domain scientists using CUDA.

Introductory: 25% Intermediate: 50% Advanced: 25%

Chair/Presenter Details:

Massimiliano Fatica
NVIDIA

David P. Luebke
NVIDIA

Ian A. Buck
NVIDIA

John D. Owens
University of California, Davis

Mark J. Harris
NVIDIA

John E. Stone
University of Illinois

James C. Phillips
University of Illinois

Bernard Deschizeaux
CGGVeritas

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