DocumentCode :
1486485
Title :
A quantitative analysis of the performance and scalability of distributed shared memory cache coherence protocols
Author :
Heinrich, Mark ; Soundararajan, Vijayaraghavan ; Hennessy, John ; Gupta, Anoop
Author_Institution :
Sch. of Electr. Eng., Cornell Univ., Ithaca, NY, USA
Volume :
48
Issue :
2
fYear :
1999
fDate :
2/1/1999 12:00:00 AM
Firstpage :
205
Lastpage :
217
Abstract :
Scalable cache coherence protocols have become the key technology for creating moderate to large-scale shared-memory multiprocessors. Although the performance of such multiprocessors depends critically on the performance of the cache coherence protocol, little comparative performance data is available. Existing commercial implementations use a variety of different protocols, including bit-vector/coarse-vector protocols, SCI-based protocols, and COMA protocols. Using the programmable protocol processor of the Stanford FLASH multiprocessor, we provide a detailed, implementation-oriented evaluation of four popular cache coherence protocols. In addition to measurements of the characteristics of protocol execution (e.g., memory overhead, protocol execution time, and message count) and of overall performance, we examine the effects of scaling the processor count from 1 to 128 processors. Surprisingly, the optimal protocol changes for different applications and can change with processor count even within the same application. These results help identify the strengths of specific protocols and illustrate the benefits of providing flexibility in the choice of cache coherence protocol
Keywords :
distributed shared memory systems; performance evaluation; protocols; COMA protocols; SCI-based protocols; Stanford FLASH multiprocessor; bit-vector/coarse-vector protocols; distributed shared memory cache coherence protocols; memory overhead; performance; quantitative analysis; scalability; shared-memory multiprocessors; Access protocols; Clocks; Coherence; Data structures; Delay; Laboratories; Large-scale systems; Performance analysis; Scalability; Time measurement;
fLanguage :
English
Journal_Title :
Computers, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9340
Type :
jour
DOI :
10.1109/12.752662
Filename :
752662
Link To Document :
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