Variable-Size Batched LU for Small Matrices and Its Integration into Block-Jacobi Preconditioning

TitleVariable-Size Batched LU for Small Matrices and Its Integration into Block-Jacobi Preconditioning
Publication TypeConference Paper
Year of Publication2017
AuthorsAnzt, H., J. Dongarra, G. Flegar, and E. S. Quintana-Orti
Conference Name46th International Conference on Parallel Processing (ICPP)
Date Published2017-08
PublisherIEEE
Conference LocationBristol, United Kingdom
Keywordsgraphics processing units, Jacobian matrices, Kernel, linear systems, Parallel processing, Sparse matrices
Abstract

We present a set of new batched CUDA kernels for the LU factorization of a large collection of independent problems of different size, and the subsequent triangular solves. All kernels heavily exploit the registers of the graphics processing unit (GPU) in order to deliver high performance for small problems. The development of these kernels is motivated by the need for tackling this embarrassingly parallel scenario in the context of block-Jacobi preconditioning that is relevant for the iterative solution of sparse linear systems.

URLhttp://ieeexplore.ieee.org/abstract/document/8025283/?reload=true
DOI10.1109/ICPP.2017.18
Project Tags: 
External Publication Flag: