DocumentCode :
2907113
Title :
Power-Performance Comparison of Single-Task Driven Many-Cores
Author :
Keceli, Fuat ; Moreshet, Tali ; Vishkin, Uzi
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Maryland, College Park, MD, USA
fYear :
2011
fDate :
7-9 Dec. 2011
Firstpage :
348
Lastpage :
355
Abstract :
Many-cores, processors with 100s of cores, are becoming increasingly popular in general-purpose computing, yet power is a limiting factor in their performance. In this paper, we compare the power and performance of two design points in the many-core processor domain. The XMT general-purpose processor provides significant runtime advantage on irregular parallel programs (e.g., graph algorithms). This was previously demonstrated and tied to its architecture choices and ease-of-programming. In contrast, current commercial GPUs excel at regular parallel programs that require high processing capability. In this work, we set the power envelope as a constraint and evaluate an envisioned 1024-core XMT processor against an NVIDIA GTX280 GPU considering various scenarios for estimating the power of the XMT chip. Even under worst-case assumptions and scenarios, simulations show that the XMT processor sustains its advantage over the GPU on irregular parallel programs, while not falling significantly behind on regular programs. The total energy spent per benchmark fits a similar pattern. Given that the two architectures target different types of parallelism, a future system can potentially utilize an XMT chip and a GPU chip in complementary roles.
Keywords :
graphics processing units; multiprocessing systems; parallel programming; performance evaluation; power aware computing; NVIDIA GTX280 GPU; XMT chip; XMT general-purpose processor; general-purpose computing; graphics processing unit; many-core processor design point; parallel program; power envelope; power-performance comparison; single-task driven many-core; Benchmark testing; Clocks; Computer architecture; Graphics processing unit; Random access memory; Temperature measurement; GPU; PRAM; XMT; many-core; parallelism; power and performance comparison;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel and Distributed Systems (ICPADS), 2011 IEEE 17th International Conference on
Conference_Location :
Tainan
ISSN :
1521-9097
Print_ISBN :
978-1-4577-1875-5
Type :
conf
DOI :
10.1109/ICPADS.2011.101
Filename :
6121297
Link To Document :
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