Optimization of the Multishift QR Algorithm with Coprocessors for Non-Hermitian Eigenvalue Problems

DOI10.4208/eajam.300510.250311azbMath1287.65026OpenAlexW2312343590MaRDI QIDQ5406891

Yoshimasa Nakamura, Yusaku Yamamoto, Shao-Liang Zhang, Takashi Uneyama, Takafumi Miyata

Publication date: 4 April 2014

Published in: Unnamed Author (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.4208/eajam.300510.250311a

zbMATH Keywords

numerical exampleseigenvaluesperformance modelingmultishift QR algorithmbulge-chasingdense, large, non-Hermitian matrix

Mathematics Subject Classification ID

Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Complexity and performance of numerical algorithms (65Y20) Numerical algorithms for specific classes of architectures (65Y10)

Cites Work

• Unnamed Item
• The Multishift QR Algorithm. Part I: Maintaining Well-Focused Shifts and Level 3 Performance
• The QR Transformation A Unitary Analogue to the LR Transformation--Part 1
• ON A BLOCK IMPLEMENTATION OF HESSENBERG MULTISHIFT QR ITERATION

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