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IJPP
2011

Regular Lattice and Small-World Spin Model Simulations Using CUDA and GPUs

11 years 8 months ago
Regular Lattice and Small-World Spin Model Simulations Using CUDA and GPUs
Data-parallel accelerator devices such as Graphical Processing Units (GPUs) are providing dramatic performance improvements over even multicore CPUs for lattice-oriented applications in computational physics. Models such as the Ising and Potts models continue to play a role in investigating phase transitions on small-world and scale-free graph structures. These models are particularly well-suited to the performance gains possible using GPUs and relatively high-level device programming languages such as NVIDIA’s Compute Unified Device Architecture (CUDA). We report on algorithms and CUDA data-parallel programming techniques for implementing Metropolis Monte Carlo updates for the Ising using bit-packing storage, and adjacency neighbour lists for various graph structures in addition to regular hypercubic lattices. We report on parallel performance gains and also memory and performance tradeoffs using GPU/CPU and algorithmic combinations.
Kenneth A. Hawick, Arno Leist, Daniel P. Playne
Added 16 May 2011
Updated 16 May 2011
Type Journal
Year 2011
Where IJPP
Authors Kenneth A. Hawick, Arno Leist, Daniel P. Playne
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