You are here: MIMS > EPrints
MIMS EPrints

2012.114: Implementing QR Factorization Updating Algorithms on GPUs

2012.114: Robert Andrew and Nicholas J. Dingle (2012) Implementing QR Factorization Updating Algorithms on GPUs.

There is a more recent version of this eprint available. Click here to view it.

Full text available as:

PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
397 Kb

Abstract

Linear least squares problems are commonly solved by QR factorization. When multiple solutions have to be computed with only minor changes in the underlying data, knowledge of the difference between the old data set and the new one can be used to update an existing factorization at reduced computational cost. This paper investigates the viability of implementing QR updating algorithms on GPUs. We demonstrate that GPU-based updating for removing columns achieves speed-ups of up to 13.5x compared with full GPU QR factorization. Other updates achieve speed-ups under certain conditions, and we characterize what these conditions are.

Item Type:MIMS Preprint
Subjects:MSC 2000 > 15 Linear and multilinear algebra; matrix theory
MSC 2000 > 65 Numerical analysis
MSC 2000 > 68 Computer science
MIMS number:2012.114
Deposited By:Dr Nicholas Dingle
Deposited On:02 December 2012

Available Versions of this Item

Download Statistics: last 4 weeks
Repository Staff Only: edit this item