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Parallel Computation Techniques for Graphical Programming Units (GPUs)

Massively multi-threaded programming on GPUs has transitioned from the niche domain of graphics computation to a wide variety of general applications. This talk will briefly review the general architecture of GPUs and the APIs used to program them before moving into a deeper discussion of the programming patterns and approaches that have been employed in effectively exploiting this unique computational platform.

About the Speaker

Dr. Gil Speyer, Scientist/Programmer, Mayo Clinic

After receiving his B.S. in electrical engineering from MIT, Gil Speyer worked on programmable logic chips at Xilinx, Inc. in San Jose, CA. He earned his Ph.D. in electrical engineering at ASU in 2005, researching transport in molecular devices. Subsequently, he worked at ASU's Advanced Computing Center as a research scientist developing parallel programs with various research groups and teaching undergraduate and graduate-level courses in parallel computing. Since June 2012, he has been a scientist programmer at the Mayo Clinic developing GPU-accelerated software solutions for a radiology research team.

Downloads

20121114_Speyer_GPU_programming.pdf