NDLI: Reduced-Bandwidth Multithreaded Algorithms for Sparse Matrix-Vector Multiplication

Content Provider	IEEE Xplore Digital Library
Author	Buluç, A. Williams, S. Oliker, L. Demmel, J.
Copyright Year	2011
Abstract	On multicore architectures, the ratio of peak memory bandwidth to peak floating-point performance (byte:flop ratio) is decreasing as core counts increase, further limiting the performance of bandwidth limited applications. Multiplying a sparse matrix (as well as its transpose in the unsymmetric case) with a dense vector is the core of sparse iterative methods. In this paper, we present a new multithreaded algorithm for the symmetric case which potentially cuts the bandwidth requirements in half while exposing lots of parallelism in practice. We also give a new data structure transformation, called bit masked register blocks, which promises significant reductions on bandwidth requirements by reducing the number of indexing elements without introducing additional fill-in zeros. Our work shows how to incorporate this transformation into existing parallel algorithms (both symmetric and unsymmetric) without limiting their parallel scalability. Experimental results indicate that the combined benefits of bit masked register blocks and the new symmetric algorithm can be as high as a factor of 3.5x in multicore performance over an already scalable parallel approach. We also provide a model that accurately predicts the performance of the new methods, showing that even larger performance gains are expected in future multicore systems as current trends (decreasing byte:flop ratio and larger sparse matrices) continue.
Starting Page	721
Ending Page	733
File Size	1489029
Page Count	13
File Format	PDF
ISBN	9781612843728
ISSN	15302075
DOI	10.1109/IPDPS.2011.73
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-05-16
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bandwidth Symmetric matrices Sparse matrices Parallel processing Registers Multicore processing Program processors
Content Type	Text
Resource Type	Article

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