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2012/08/16, MC103, 12 - 12:30
Portable Matrix Operation Library for GPUs
Rahul
Garg
, PhD Student, SABLE lab, McGill
Area:
Programming Languages and Scientific Computing
Abstract:
Does your work involve matrix operations with large dense matrices? Not satisfied
with speed you are getting on CPUs? Then you may be aware that modern GPUs provide
considerably better performance on many types of matrix computations than most CPUs.
However, so far you had to choose vendor-specific APIs (eg: Nvidia CUBLAS only works
on Nvidia) making your code non-portable. I present a high-performance portable BLAS
library that runs on many GPUs including AMD, Nvidia and Intel GPUs. I will present
initial performance results, and discuss future plans.
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