Toward a Generic Hybrid CPU-GPU Parallelization of Divide-and-Conquer Algorithms-Reference-Cited by-同舟云学术

Toward a Generic Hybrid CPU-GPU Parallelization of Divide-and-Conquer Algorithms

Published:2014 Issue:1 Volume:4 Page:131-150
ISSN:2185-2839
Container-title:International Journal of Networking and Computing
language:en
Short-container-title:IJNC

Author:

López-Ortiz Alejandro¹,Salinger Alejandro²,Suderman Robert¹

Affiliation:

1. University of Waterloo

2. Saarland University

Publisher

IJNC Editorial Committee

Link

https://www.jstage.jst.go.jp/article/ijnc/4/1/4_131/_pdf

Reference34 articles.

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2. [2] E. Agullo, C. Augonnet, J. Dongarra, M. Faverge, H. Ltaief, S. Thibault, and S. Tomov. QR factorization on a multicore node enhanced with multiple GPU accelerators. In 25th IEEE International Symposium on Parallel and Distributed Processing, IPDPS'11, pages 932 -943, May 2011.

3. [3] E. Agullo, C. Augonnet, J. Dongarra, H. Ltaief, R. Namyst, S. Thibault, and S. Tomov. Faster, Cheaper, Better - a Hybridization Methodology to Develop Linear Algebra Software for GPUs. In W. mei W. Hwu, editor, GPU Computing Gems, volume 2. Morgan Kaufmann, Sep. 2010.

4. [4] AMD. The industry-changing impact of accelerated computing. AMD Whitepaper, Advance Micro Devices, 2008. 09/04/2011.

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