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[Harvard CS264] 10a - Easy, Effective, Efficient: GPU Programming in Python with PyOpenCL and PyCUDA (Andreas Kloeckner, NYU)

by on Apr 01, 2011

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http://cs264.org ...

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Abstract:

High-level scripting languages are in many ways polar opposites to
GPUs. GPUs are highly parallel, subject to hardware subtleties, and
designed for maximum throughput, and they offer a tremendous advance
in the performance achievable for a significant number of
computational problems. On the other hand, scripting languages such as
Python favor ease of use over computational speed and do not generally
emphasize parallelism. PyOpenCL and PyCUDA are two packages that
attempt to join the two together. By showing concrete examples, both
at the toy and the whole-application level, this talk aims to
demonstrate that by combining these opposites, a programming
environment is created that is greater than just the sum of its two
parts.

Speaker biography:

Andreas Klöckner obtained his PhD degree working with Jan Hesthaven at
the Department of Applied Mathematics at Brown University. He worked
on a variety of topics all aiming to broaden the utility of
discontinuous Galerkin (DG) methods. This included their use in the
simulation of plasma physics and the demonstration of their particular
suitability for computation on throughput-oriented graphics processors
(GPUs). He also worked on multi-rate time stepping methods and shock
capturing schemes for DG.

In the fall of 2010, he joined the Courant Institute of Mathematical
Sciences at New York University as a Courant Instructor. There, he is
working on problems in computational electromagnetics with Leslie
Greengard.

His research interests include:

- Discontinuous Galerkin and integral equation methods for wave
propagation

- Programming tools for parallel architectures

- High-order unstructured particle-in-cell methods for plasma simulation

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[Harvard CS264] 10a - Easy, Effective, Efficient: GPU Programming in Python with PyOpenCL and PyCUDA (Andreas Kloeckner, NYU) [Harvard CS264] 10a - Easy, Effective, Efficient: GPU Programming in Python with PyOpenCL and PyCUDA (Andreas Kloeckner, NYU) Presentation Transcript