Parallel Sparse Cholesky Factorization on a Heterogeneous Platform

Dan ZOU  Yong DOU  Rongchun LI  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E96-A   No.4   pp.833-834
Publication Date: 2013/04/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.E96.A.833
Print ISSN: 0916-8508
Type of Manuscript: LETTER
Category: Algorithms and Data Structures
Keyword: 
sparse Cholesky factorization,  supernodal method,  GPU,  

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Summary: 
We present a new approach for sparse Cholesky factorization on a heterogeneous platform with a graphics processing unit (GPU). The sparse Cholesky factorization is one of the core algorithms of numerous computing applications. We tuned the supernode data structure and used a parallelization method for GPU tasks to increase GPU utilization. Results show that our approach substantially reduces computational time.