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Understanding application performance on shared virtual memory systems
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Source International Symposium on Computer Architecture archive
Proceedings of the 23rd annual international symposium on Computer architecture table of contents
Philadelphia, Pennsylvania, United States
Pages: 122 - 133  
Year of Publication: 1996
ISBN:0-89791-786-3
Also published in ...
Authors
Liviu Iftode  Department of Computer Science, Princeton University, Princeton, NJ
Jaswinder Pal Singh  Department of Computer Science, Princeton University, Princeton, NJ
Kai Li  Department of Computer Science, Princeton University, Princeton, NJ
Sponsors
IEEE-CS\TCCA : TC on Computer Arhitecture
SIGARCH: ACM Special Interest Group on Computer Architecture
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 19,   Downloads (12 Months): 48,   Citation Count: 18
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ABSTRACT

Many researchers have proposed interesting protocols for shared virtual memory (SVM) systems, and demonstrated performance improvements on parallel programs. However, there is still no clear understanding of the performance potential of SVM systems for different classes of applications. This paper begins to fill this gap, by studying the performance of a range of applications in detail and understanding it in light of application characteristics.We first develop a brief classification of the inherent data sharing patterns in the applications, and how they interact with system granularities to yield the communication patterns relevant to SVM systems. We then use detailed simulation to compare the performance of two SVM approaches---Lazy Released Consistency (LRC) and Automatic Update Release Consistency (AURC)---with each other and with an all-hardware CC-NUMA approach. We examine how performance is affected by problem size, machine size, key system parameters, and the use of less optimized program implementations. We find that SVM can indeed perform quite well for systems of at leant up to 32 processors for several nontrivial applications. However, performance is much more variable across applications than on CC-NUMA systems, and the problem sizes needed to obtain good parallel performance are substantially larger. The hardware-assisted AURC system tends to perform significantly better than the all-software LRC under our system assumptions, particularly when realistic cache hierarchies are used.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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B.N. Bershad, M.J. Zekauskas, and W.A. Sawdon. The Midway Distributed Shared Memory System. in Proceedings of the IEEE COMPCON '93 Conference, February 1993.
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L. Iftode, J.P. Singh, and K. Li. irregular Applications under Software Shared Memory. Technical Report TR-514-96, Princeton, N J, February 1996.
 
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L. Iftode, J.P. Singh, and K. Li. Scope Consistency: a Bridge between Release Consistency and Entry Consistency. Technical Report TR-509-96, Princeton, NJ, January 1996.
 
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P. Keleher, A.L. Cox, S. Dwarkadas, and W. Zwaenepoel. TreadMarks: Distributed Shared Memory on Standard Workstations and Operating Systems. In Proceedings of the Winter USENIX Conference, pages 115-132, January 1994.
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CITED BY  19

Collaborative Colleagues:
Liviu Iftode: colleagues
Jaswinder Pal Singh: colleagues
Kai Li: colleagues