DocumentCode :
1606990
Title :
Energy and performance tradeoffs for matrix multiplication on multicore machines
Author :
Wang, Zhe ; Tan, Hengxing ; Ranka, Sanjay
Author_Institution :
Dept. of Comput. & Inf. Sci. & Eng., Univ. of Florida, Gainesville, FL, USA
fYear :
2012
Firstpage :
1
Lastpage :
6
Abstract :
In this paper, we propose a general methodology for energy estimation of bus-based multi-core processors assuming that DVS can be used for both buses and cores. Our formulation can provide tradeoffs between DVS setting for buses and cores. We examine this methodology using various parallel matrix multiplication algorithms that are suitable for shared memory multicore machines with L1 and L2 caches. Our simulation results show that the simultaneously changing the voltage of buses along with cores can result in 10 - 20% reduction in the overall energy requirements as compared to only changing the core voltages. This is under the assumption that sufficient slack is available for DVS to be able to work at lower voltages to save energy. The methods proposed in this paper demonstrate the usefulness of multiple element optimization in multicore architectures. The experiments show that a good understanding of the overall tradeoffs between the effect of these elements in the overall performance and energy requirements can lead to improved results in the energy requirements.
Keywords :
energy conservation; matrix multiplication; memory architecture; multiprocessing systems; power aware computing; system buses; DVS; L1 cache; L2 cache; bus voltage; bus-based multicore processors; core voltage; dynamic voltage scaling; energy estimation; energy requirement reduction; energy tradeoff; multicore architectures; multiple element optimization; parallel matrix multiplication algorithms; performance requirements; performance tradeoff; shared memory multicore machines; Clocks; Energy consumption; Memory management; Multicore processing; Partitioning algorithms; Time frequency analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Green Computing Conference (IGCC), 2012 International
Conference_Location :
San Jose, CA
Print_ISBN :
978-1-4673-2155-6
Electronic_ISBN :
978-1-4673-2153-2
Type :
conf
DOI :
10.1109/IGCC.2012.6322295
Filename :
6322295
Link To Document :
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