Title
Hierarchical Parallel Matrix Multiplication on Large-Scale Distributed Memory Platforms
Abstract
Matrix multiplication is a very important computation kernel both in its own right as a building block of many scientific applications and as a popular representative for other scientific applications. Cannon's algorithm which dates back to 1969 was the first efficient algorithm for parallel matrix multiplication providing theoretically optimal communication cost. However this algorithm requires a square number of processors. In the mid-1990s, the SUMMA algorithm was introduced. SUMMA overcomes the shortcomings of Cannon's algorithm as it can be used on a nonsquare number of processors as well. Since then the number of processors in HPC platforms has increased by two orders of magnitude making the contribution of communication in the overall execution time more significant. Therefore, the state of the art parallel matrix multiplication algorithms should be revisited to reduce the communication cost further. This paper introduces a new parallel matrix multiplication algorithm, Hierarchical SUMMA (HSUMMA), which is a redesign of SUMMA. Our algorithm reduces the communication cost of SUMMA by introducing a two-level virtual hierarchy into the two-dimensional arrangement of processors. Experiments on an IBM Blue Gene/P demonstrate the reduction of communication cost up to 2.08 times on 2048 cores and up to 5.89 times on 16384 cores.
Year
DOI
Venue
2013
10.1109/ICPP.2013.89
international conference on parallel processing
Keywords
DocType
Volume
communication cost,theoretically optimal communication cost,art parallel matrix multiplication,parallel matrix multiplication,summa algorithm,new parallel matrix multiplication,scientific application,matrix multiplication,hierarchical summa,memory platforms,efficient algorithm,parallel algorithms
Conference
abs/1306.4161
ISSN
Citations 
PageRank 
0190-3918
5
0.46
References 
Authors
8
3
Name
Order
Citations
PageRank
Jean-Noël Quintin1284.11
Khalid Hasanov2283.35
Alexey Lastovetsky376384.50