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dc.contributor.authorMarin, Gabriel
Mellor-Crummey, John
dc.date.accessioned 2017-08-02T22:03:05Z
dc.date.available 2017-08-02T22:03:05Z
dc.date.issued 2007-10-05
dc.identifier.urihttps://hdl.handle.net/1911/96362
dc.description.abstract The potential for improving the performance of data-intensive scientific programs by enhancing data reuse in cache is substantial because CPUs are significantly faster than memory. Traditional performance tools typically collect or simulate cache miss counts or rates and attribute them at the function level. While such information identifies program scopes that suffer from poor data locality, it is often insufficient to diagnose the causes for poor data locality and to identify what program transformations would improve memory hierarchy utilization. This paper describes a memory reuse distance based approach that identifies an application’s most significant memory access patterns causing cache misses and provides insight into ways of improving data reuse. We demonstrate the effectiveness of this analysis for two scientific codes: one for simulating neutron transport and a second for simulating turbulent transport in burning plasmas. Our tools pinpointed opportunities for enhancing data reuse. Using this feedback as a guide, we transformed the codes, reducing their misses at various levels of the memory hierarchy by integer factors and reducing their execution time by as much as 60% and 33%, respectively.
dc.format.extent 17 pp
dc.language.iso eng
dc.rights You are granted permission for the noncommercial reproduction, distribution, display, and performance of this technical report in any format, but this permission is only for a period of forty-five (45) days from the most recent time that you verified that this technical report is still available from the Computer Science Department of Rice University under terms that include this permission. All other rights are reserved by the author(s).
dc.title Understanding Unfulfilled Memory Reuse Potential in Scientific Applications
dc.type Technical report
dc.date.note October 5, 2007
dc.identifier.digital TR07-6
dc.type.dcmi Text
dc.identifier.citation Marin, Gabriel and Mellor-Crummey, John. "Understanding Unfulfilled Memory Reuse Potential in Scientific Applications." (2007) https://hdl.handle.net/1911/96362.


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