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Measuring parallel processor performance
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Communications of the ACM archive
Volume 33 ,  Issue 5  (May 1990) table of contents
Pages: 539 - 543  
Year of Publication: 1990
ISSN:0001-0782
Authors
Alan H. Karp  IBM Scientific Center, Palo Alto, CA
Horace P. Flatt  IBM Scientific Center, Palo Alto, CA
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 13,   Downloads (12 Months): 117,   Citation Count: 24
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ABSTRACT

Many metrics are used for measuring the performance of a parallel algorithm running on a parallel processor. This article introduces a new metric that has some advantages over the others. Its use is illustrated with data from the Linpack benchmark report and the winners of the Gordon Bell Award.


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.

 
1
Amdahl. G.M. Validitv of the single processor approach to achieving large scale cornputer ~apabililie, s. In Prot't'c,lings of AFIPS Spring joint Comtputer Conference. 30. Atlantic Citv, NIL 1967.
 
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Flatt. H.P.. and Kenileclv. K. Performance of parallel processors. Parallel Comput.12, (Oct. 1989}, '1-20.
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Gustafson. J.J ancl Montry, (;.R.. and Brenner. R.E. Developmellt of parallel met hods for a 1024-processor hypercube. SIAM Cci. Star. Comp. 9. {luly 1988), 609-638.

CITED BY  24


REVIEW

"Thomas C. Richards : Reviewer"

Karp and Flatt examine an alternative method of measuring parallel processor performance. They define a serial fraction metric and show that it provides information not revealed by other commonly used metrics, including elapsed time to run, pr  more...

Collaborative Colleagues:
Alan H. Karp: colleagues
Horace P. Flatt: colleagues