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

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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