The Relevance of New Data Structure Approaches for Dense Linear Algebra in the New Multi-Core / Many Core Environments
- Cite this paper as:
- Gustavson F.G. (2008) The Relevance of New Data Structure Approaches for Dense Linear Algebra in the New Multi-Core / Many Core Environments. In: Wyrzykowski R., Dongarra J., Karczewski K., Wasniewski J. (eds) Parallel Processing and Applied Mathematics. PPAM 2007. Lecture Notes in Computer Science, vol 4967. Springer, Berlin, Heidelberg
For about ten years now, Bo Kågström’s Group in Umea, Sweden, Jerzy Waśniewski’s Team at Danish Technical University in Lyngby, Denmark, and I at IBM Research in Yorktown Heights have been applying recursion and New Data Structures (NDS) to increase the performance of Dense Linear Algebra (DLA) factorization algorithms. Later, John Gunnels, and later still, Jim Sexton, both now at IBM Research also began working in this area. For about three years now almost all computer manufacturers have dramatically changed their computer architectures which they call Multi-Core, (MC). It turns out that these new designs give poor performance for the traditional designs of DLA libraries such as LAPACK and ScaLAPACK. Recent results of Jack Dongarra’s group at the Innovative Computing Laboratory in Knoxville, Tennessee have shown how to obtain high performance for DLA factorization algorithms on the Cell architecture, an example of an MC processor, but only when they used NDS. In this talk we will give some reasons why this is so.
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