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

2. What is a GPU? 2

4. 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

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

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

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

8. 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

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

10. 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

11. 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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