%0 Conference Paper
%A Di Napoli, Edoardo
%A Berljafa, Mario
%T Parallel block Chebyshev subspace iteration algorithm optimized for sequences of correlated dense eigenproblems
%M FZJ-2012-00907
%D 2012
%X In many material science applications simulations are made of dozens of sequences, where each sequence groups together eigenproblems with increasing self-consistent cycle outer-iteration index. Successive eigenproblems in a sequence possess a high degree of correlation. In particular it has been demonstrated that eigenvectors of adjacent eigenproblems become progressively more collinear to each other as the outer-iteration index increases. This result suggests one could use eigenvectors, computed at a certain outer-iteration, as approximate solutions to improve the performance of the eigensolver at the next one. In order to opti- mally exploit the approximate solution, we developed a block iterative eigensolver augmented with a Chebyshev polynomial accelerator (BChFSI). Numerical tests show that, when the sequential version of the solver is fed approximate solutions instead of random vectors, it achieves up to a 5X speedup. Moreover the parallel shared memory implementation of the algorithm obtains a high level of efficiency up to 80 \% of the theoretical peak performance. Despite the eigenproblems in the sequence being relatively large and dense, the parallel BChFSI fed with ap- proximate solutions performs substantially better than the corresponding direct eigensolver, even for a significant portion of the sought-after spectrum
%B 5th International Conference of the ERCIM Working Group
%C 2 Dec 2012 - 2 Dec 2012, Oviedo (Spain)
Y2 2 Dec 2012 - 2 Dec 2012
M2 Oviedo, Spain
%F PUB:(DE-HGF)6
%9 Conference Presentation
%U https://juser.fz-juelich.de/record/127961