Improving data locality of the nonsymmetric QR algorithm

Simple item page
dc.contributor.advisorvan de Geijn, Roberten
dc.contributor.advisorArbogast, Todden
dc.contributor.advisorQuintana-Orti, Enrique S.en
dc.creatorJia, Kevinen
dc.date.accessioned2013-12-06T20:26:37Zen
dc.date.available2013-12-06T20:26:37Zen
dc.date.issued2013en
dc.description.abstractThe QR algorithm computes the Schur decomposition of a matrix and is the most popular algorithm for solving eigenvalue problems for dense nonsymmetric matrices. The algorithm suffers from a memory access bottleneck though. By restructuring the application of Householder reflectors to the transformation matrix in the nonsymmetric QR algorithm, data locality can be improved, increasing performance. This improvement is demonstrated against the LAPACK implementation of the implicit QR algorithm for nonsymmetric matrices, DLAHQR.en
dc.description.departmentComputer Science
dc.identifier.urihttp://hdl.handle.net/2152/22583en
dc.language.isoengen
dc.subjectQR algorithmen
dc.subjectLAPACKen
dc.subjectdata localityen
dc.titleImproving data locality of the nonsymmetric QR algorithmen
dc.typeThesisen

Access full-text files

Original bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
nonsymQR_KevinJia_final.pdf
Size:
150.73 KB
Format:
Adobe Portable Document Format
Download

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.66 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Honors Theses