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LinBox and future high performance computer algebra

Published: 27 July 2007 Publication History

Abstract

Computer chip design is entering an era in which further increases in computational power will come by increased on-chip parallelism through multi-core architectures rather than by increasing clock speed. If high performance computer algebra tools are to be offered, they must keep pace with this reality. LinBox is a library for exact linear algebra computation with integer matrices and matrices over finite fields. We discuss how LinBox design can be adapted for distributed and multi-core computation.

References

[1]
A. Buttari, J. Kurzak, and J. Dongarra. Targeting multi-core architectures for linear algebra applications. In Supercomputer 2006, page 162, Tampa, Florida, 2006. ACM Press.
[2]
J. Dongarra, D. Gannon, G. Fox, and K. Kennedy. The impact of multicore on computational science software. Technical report, Indiana University, 2007.
[3]
J-G. Dumas, B. D. Saunders, and G. Villard. Integer smith form via the valence: Experience with large sparse matrices from homology. In ISSAC 2000, pages 95--05. ACM Press, 2000.
[4]
J-G. Dumas, B. D. Saunders, and G. Villard. On efficient sparse integer matrix smith normal form computations. JSC, 32:71--99, 2001.
[5]
J. R. Johnson, W. Krandick, K. Lynch, D. G. Richardson, and A. D. Ruslanov. High-performance implementations of the descartes method. In ISSAC 2006, pages 154--161, Genoa, Italy, 2006. ACM Press.
[6]
M. Puschel, J. M. F. Moura, B. Singer, J. Xiong, J. Johnson, D. Padua, M. Veloso, and R. W. Johnson. SPIRAL: A generator for platform-adapted libraries of signal processing algorithms. Int.J.High Perform.Comput.Appl., 18(1):21--45, 2004.
[7]
B. D. Saunders and Z. Wan. Smith normal form of dense integer matrices, fast algorithms into practice. In ISSAC 2004, pages 274--281. ACM Press, 2004.
[8]
R. Vuduc, J. W. Demmel, and K. A. Yelick. Oski: A library of automatically tuned sparse matrix kernels. In SciDAC 2005, Journal of Physics: Conference Series, San Francisco, CA, USA, 2005. Institute of Physics Publishing.
[9]
R. C. Whaley, A. Petitet, and J. Dongarra. Automated empirical optimizations of software and the atlas project. Parallel Computing, 27(1-2):3--35, 2001/1.

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cover image ACM Conferences
PASCO '07: Proceedings of the 2007 international workshop on Parallel symbolic computation
July 2007
116 pages
ISBN:9781595937414
DOI:10.1145/1278177
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 July 2007

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  1. high performance
  2. multi-core
  3. parallel computation

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