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Greg Herschlag : A tutorial for CUDA programming on GPUs (Apr 17, 2017 11:55 AM)

Graphics processing units (GPUs) are powerful accelerators that can launch many processes in parallel. Over the past decade, they have been utilized for scientific computation, including molecular dynamics, fluid mechanics, machine learning, and stochastic differential equations. Although dependent on the algorithm, GPUs may execute code faster than CPUs by several orders of magnitude. The mathematics department at Duke hosts 4 older generation GPUs on two nodes that are available for department use. In this seminar I will briefly introduce how GPUs are different than CPUs; the bulk of my time will be a tutorial on how to code CUDA so that attendees may begin to take advantage of these departmental resources for their research. Depending on the attendance, it may be a hands-on tutorial so bring your laptop.

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