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Using GPU's to accelerate stencil-based computation kernels for the development of large scale scientific applications on heterogeneous systems

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Published:25 February 2012Publication History
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Abstract

We present CaCUDA - a GPGPU kernel abstraction and a parallel programming framework for developing highly efficient large scale scientific applications using stencil computations on hybrid CPU/GPU architectures. CaCUDA is built upon the Cactus computational toolkit, an open source problem solving environment designed for scientists and engineers. Due to the flexibility and extensibility of the Cactus toolkit, the addition of a GPGPU programming framework required no changes to the Cactus infrastructure, guaranteeing that existing features and modules will continue to work without modification. CaCUDA was tested and benchmarked using a 3D CFD code based on a finite difference discretization of Navier-Stokes equations.

References

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  1. Using GPU's to accelerate stencil-based computation kernels for the development of large scale scientific applications on heterogeneous systems

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        • Published in

          cover image ACM SIGPLAN Notices
          ACM SIGPLAN Notices  Volume 47, Issue 8
          PPOPP '12
          August 2012
          334 pages
          ISSN:0362-1340
          EISSN:1558-1160
          DOI:10.1145/2370036
          Issue’s Table of Contents
          • cover image ACM Conferences
            PPoPP '12: Proceedings of the 17th ACM SIGPLAN symposium on Principles and Practice of Parallel Programming
            February 2012
            352 pages
            ISBN:9781450311601
            DOI:10.1145/2145816

          Copyright © 2012 Authors

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          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 25 February 2012

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