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      GPU computing for 2-d spin systems: CUDA vs OpenGL

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          Abstract

          In recent years the more and more powerful GPU's available on the PC market have attracted attention as a cost effective solution for parallel (SIMD) computing. CUDA is a solid evidence of the attention that the major companies are devoting to the field. CUDA is a hardware and software architecture developed by Nvidia for computing on the GPU. It qualifies as a friendly alternative to the approach to GPU computing that has been pioneered in the OpenGL environment. We discuss the application of both the CUDA and the OpenGL approach to the simulation of 2-d spin systems (XY model).

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          Author and article information

          Journal
          2008-11-13
          Article
          0811.2111
          b6a3d5f3-5658-4179-9178-78b7b5529e04

          http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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          Custom metadata
          PoS LATTICE2008:024,2008
          7 pages, 1 figure; Talk presented at the XXVI Symposium on Lattice Field Theory, Williamsburg, Virginia, USA, July 14-19 2008
          hep-lat

          High energy & Particle physics
          High energy & Particle physics

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