Towards Dense Linear Algebra for Hybrid GPU Accelerated Manycore Systems
University of Tennessee (USA)
Parallel Computing, Volume 36, Issues 5-6, June 2010, Pages 232-240 (28 December 2009)
@article{tomov2010towards,
title={Towards dense linear algebra for hybrid GPU accelerated manycore systems},
author={Tomov, S. and Dongarra, J. and Baboulin, M.},
journal={Parallel Computing},
volume={36},
number={5-6},
pages={232–240},
issn={0167-8191},
year={2010},
publisher={Elsevier}
}
We highlight the trends leading to the increased appeal of using hybrid multicore+GPU systems for high performance computing. We present a set of techniques that can be used to develop efficient dense linear algebra algorithms for these systems. We illustrate the main ideas with the development of a hybrid LU factorization algorithm where we split the computation over a multicore and a graphics processor, and use particular techniques to reduce the amount of pivoting and communication between the hybrid components. This results in an efficient algorithm with balanced use of a multicore processor and a graphics processor.
November 8, 2010 by hgpu