A Performance Evaluation of QR-eigensolver on IBM Roadrunner cluster for Large Sparse Matrices

A Performance Evaluation of QR-eigensolver on IBM Roadrunner cluster for Large Sparse Matrices

The paper presents a performance analysis of theQR eigensolver from ScaLAPACK library on the IBMRoadrunner machine. A ScaLAPACK-based testing platformwas developed in order to evaluate the performance of a parallelsolver to compute the eigenvalues and eigenvectors for largescalesparse matrices. Our...

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Bibliographic Details
Main Authors: Ionela RUSU, Stefan Gh. PENTIUC, Elena Gina CRACIUN, Stefania SOIMAN
Format: Article
Language:English
Published: Stefan cel Mare University of Suceava 2013-01-01
Series:Journal of Applied Computer Science & Mathematics
Subjects:
eigenvalues
high performance computing
QR factorization
systems of linear equations
ScaLAPACK
Online Access:http://jacs.usv.ro/getpdf.php?paperid=14_6

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