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2015 | OriginalPaper | Buchkapitel

Performance Analysis of the Householder-Type Parallel Tall-Skinny QR Factorizations Toward Automatic Algorithm Selection

verfasst von : Takeshi Fukaya, Toshiyuki Imamura, Yusaku Yamamoto

Erschienen in: High Performance Computing for Computational Science -- VECPAR 2014

Verlag: Springer International Publishing

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Abstract

We consider computing tall-skinny QR factorizations on a large-scale parallel machine. We present a realistic performance model and analyze the difference of the parallel execution time between Householder QR and TSQR. Our analysis indicates the possibility that TSQR becomes slower than Householder QR as the number of columns of the target matrix increases. We aim for estimating the difference and selecting the faster algorithm by using models, which falls into auto-tuning. Numerical experiments on the K computer support our analysis and show our success in determining the faster algorithm.

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Fußnoten
1
Operated at the RIKEN Advanced Institute for Computational Science.
 
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Metadaten
Titel
Performance Analysis of the Householder-Type Parallel Tall-Skinny QR Factorizations Toward Automatic Algorithm Selection
verfasst von
Takeshi Fukaya
Toshiyuki Imamura
Yusaku Yamamoto
Copyright-Jahr
2015
DOI
https://doi.org/10.1007/978-3-319-17353-5_23