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 National Science
Foundation Award #0509521 |
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CSE--SMA: Understanding the Performance of Modern Systems |
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| Investigator(s): |
Amer Diwan (PI)
; Michael Mozer (Co-PI)
; Peter Sweeney (Co-PI)
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| Sponsor: |
University of Colorado at Boulder, CO 80309 3034926221
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| Start Date/Expiration Date |
2005-08-01 to 2009-07-31 (amended 2005-06-30) |
| Awarded Amount to Date: |
$400,000 |
| Abstract: The proposed work will develop, implement, and evaluate new techniques that help to automate performance analysis of modern software systems. The methodology pursued breaks down the problem of automating performance analysis into three components: identifying performance anomalies, detecting covariation between performance metrics, and determining causality between covariant metrics. The proposed approach uses statistical data mining and machine learning techniques to automate the three components. The proposed system works on a collection of traces, with each trace containing one or more streams of measurements from a performance metric.
The project will bring techniques from the statistical data mining and machine learning techniques to bear on the problem of automating performance analysis. The fundamental insight of the proposed approach is that there is significant information in the time-varying contours of a stream. Previous statistical approaches to performance analysis have ignored this information in favor of examining the covariation across metrics at a particular snapshot of time. |
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| NSF Org: |
CNS - Division of Computer and Network Systems |
| Award Number: |
0509521 |
| Award Instrument: |
Standard Grant |
| Program Manager: |
Frederica Darema
CNS Division of Computer and Network Systems
CSE Directorate for Computer & Information Science & Engineering
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| NSF Program(s): |
ITR-HEC |
| Field Application(s): |
Computer Science |
| Program Reference Code(s): |
BASIC RESEARCH & HUMAN RESORCS, 9218
NEXT GENERATION SOFTWARE PROGR, 2884 |
| Program Element Code(s): |
7469 |
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