GPU Computing Jan Just Keijser Nikhef Jamboree, Utrecht

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Presentation transcript:

GPU Computing Jan Just Keijser Nikhef Jamboree, Utrecht 10 December 2012 1

What is a GPU? 2

What can you do with a GPU? From: Massively Parallel Computing with CUDA GPUs are excellent for performing the Same operation (Instruction) on Multiple Data elements (SIMD) Vector processing, anyone? 4

How do you program a GPU? From: An Introduction to GPU Computing and CUDA Architecture 5

How do you program a GPU? From: An Introduction to GPU Computing and CUDA Architecture 6

How do you program a GPU? From: An Introduction to GPU Computing and CUDA Architecture 7

Programming languages NVIDIA CUDA AMD/ATI Stream Computing Open standard: OpenCL Supported by NVIDIA, AMD, Intel, ARM Language bindings C/C++ FORTRAN Python, Perl R, MATLAB, Mathematica 8

Possible applications Fluid dynamics Tomography Monte Carlo simulations Chroma Library for Lattice Field Theory ... ? At Nikhef: ANTARES/KM3NET VIRGO ... ? 9

No silver bullet Requires code rewrite and optimization GPU architectures rapidly change, so do the optimization techniques Limited by amount of memory on the GPU card (≤ 8 GB) Number of cores on a CPU is also rapidly increasing 10

Available GPUs @ Nikhef Some desktops already have a GPU! NVIDIA Quadro NVS290 (low end) AMD Firepro V5900 1 server with 2 x NVIDIA Tesla M2070 Q2 2013: Intel Xeon Phi testboard Elsewhere in the Netherlands: SARA: GPU cluster (Tesla C1070) RuG: GPU cluster Successor to Huygens will use GPUs Leiden: Little Green Machine 11

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