Document Type
Conference Proceeding
Language
eng
Format of Original
7 p.
Publication Date
2012
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Source Publication
41st International Conference on Parallel Processing Workshops (ICPPW)
Source ISSN
1530-2016
Original Item ID
doi: 10.1109/ICPPW.2012.36
Abstract
Excessive energy consumption has become one of the major challenges in high performance computing. Reducing the energy consumption of frequently used high performance computing applications not only saves the energy cost but also reduces the greenhouse gas emissions. This paper focuses on developing energy efficient algorithms and software for the widely used matrix-matrix multiplication, so that it is able to consume less energy in a DVFS-enabled cluster with little sacrifice in performance. The state-of-the-art practical parallel matrix matrix multiplication algorithm in ScaLAPACK partitions matrices into small blocks and distributes matrices using a two dimensional block cyclic distribution approach. Experimental results demonstrate that our energy efficient matrix-matrix multiplication algorithm can save up to 26.35% of energy with about 1% performance penalty. And the modified PDGEMM of ScaLAPACK is able to save energy more than 20% with less than 2% of performance loss.
Recommended Citation
Chen, Longxiang; Wu, Panruo; Chen, Zizhong; and Ge, Rong, "Energy Efficient Parallel Matrix-Matrix Multiplication for DVFS-Enabled Clusters" (2012). Mathematics, Statistics and Computer Science Faculty Research and Publications. 91.
https://epublications.marquette.edu/mscs_fac/91
Comments
Accepted version. Published as part of the proceedings of the conference 41st International Conference on Parallel Processing Workshops (ICPPW), 2012: 239-245. DOI. © 2012 Institute of Electrical and Electronics Engineers (IEEE). Used with permission.