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Implementation of Parallel Processing Techniques on Graphical Processing Units Poster C.4

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Implementation of Parallel Processing Techniques on Graphical Processing Units Poster C.4. Brad Baker, Wayne Haney, Dr. Charles Choi. Industry Direction. High performance COTS computing is moving to multi-core and heterogeneous silicon. Multi-core CPU with smaller individual cores

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Implementation of Parallel Processing Techniques on Graphical Processing Units Poster C.4

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  1. Implementation of Parallel Processing Techniques on Graphical Processing UnitsPoster C.4 Brad Baker, Wayne Haney, Dr. Charles Choi

  2. Industry Direction • High performance COTS computing is moving to multi-core and heterogeneous silicon • Multi-core CPU with smaller individual cores • GPU co-processor • Multi-core CPU with 1-3 GPU co-processors • Heterogeneous multi-core (IBM Cell) • Smaller, heterogeneous cores on same silicon

  3. Nvidia Cuda Platform • Utilizes most powerful GPU on market • Most extensive pre-built math library Approx. 50% Performance Gain Using CUDA’s FFT Math Benchmark and Signal Processing String Results

  4. Implementation of Parallel Processing Techniques on Graphical Processing UnitsPoster C.4 Brad Baker, Wayne Haney, Dr. Charles Choi

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