EECS Publication
Scheduling Two-sided Transformations using Tile Algorithms on Multicore Architectures
Hatem Ltaief, Jakub Kurzak, and Jack Dongarra
The objective of this paper is to describe, in the context of multi-core architectures, different scheduler implementations for the two-sided linear algebra transformations, in particular the Hessenberg and Bidiagonal reductions which are the first steps for the standard eigenvalue problems and the singular value decompositions respectively. State-of-the-art dense linear algebra softwares, such as the LAPACK and ScaLAPACK libraries, suffer performance losses on multi-core processors due to their inability to fully exploit thread-level parallelism. At the same time the coarse-grain dataflow model gains popularity as a paradigm for programming multi-core architectures. By using the concepts of algorithms-by-tiles [Buttari et al., 2007] along with efficient mechanisms for data-driven execution, these two-sided reductions achieve high performance computing. The main drawback of the algorithms-bytiles approach for two-sided transformations is that the full reduction can not be obtained in one stage. Other methods have to be considered to further reduce the band matrices to the required forms.
Published 2009-02-11 05:00:00 as ut-cs-09-637 (ID:69)