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Parallel Variants of the Multishift QZ Algorithm with Advanced Deflation Techniques
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Högpresterande beräkningscentrum norr (HPC2N).
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Högpresterande beräkningscentrum norr (HPC2N).
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Högpresterande beräkningscentrum norr (HPC2N).
2007 (engelsk)Inngår i: Applied Parallel Computing - State of the Art in Scientific Computing: 8th International Workshop, PARA 2006, Springer , 2007, s. 117-126Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

The QZ algorithm reduces a regular matrix pair to generalized Schur form, which can be used to address the generalized eigenvalue problem. This paper summarizes recent work on improving the performance of the QZ algorithm on serial machines and work in progress on a novel parallel implementation. In both cases, the QZ iterations are based on chasing chains of tiny bulges. This allows to formulate the majority of the computation in terms of matrix-matrix multiplications, resulting in natural parallelism and better performance on modern computing systems with memory hierarchies. In addition, advanced deflation strategies are used, specifically the so called aggressive early deflation, leading to a considerable convergence acceleration and consequently to a reduction of floating point operations and computing time.

sted, utgiver, år, opplag, sider
Springer , 2007. s. 117-126
Serie
Lecture Notes in Computer Science ; LNCS 4699
Identifikatorer
URN: urn:nbn:se:umu:diva-23166OAI: oai:DiVA.org:umu-23166DiVA, id: diva2:220756
Tilgjengelig fra: 2009-06-02 Laget: 2009-06-02 Sist oppdatert: 2018-06-08

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Adlerborn, BjörnKågström, Bo

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