Abstract
Due to cost, time, and flexibility constraints, simulators are often used to explore the design space when developing new processor architectures, as well as when evaluating the performance of new processor enhancements. However, despite this dependence on simulators, statistically rigorous simulation methodologies are not typically used in computer architecture research. A formal methodology can provide a sound basis for drawing conclusions gathered from simulation results by adding statistical rigor, and consequently, can increase confidence in the simulation results. This paper demonstrates the application of a rigorous statistical technique to the setup and analysis phases of the simulation process. Specifically, we apply a Plackett and Burman design to: (1) identify key processor parameters; (2) classify benchmarks based on how they affect the processor; and (3) analyze the effect of processor performance enhancements. Our technique expands on previous work by applying a statistical method to improve the simulation methodology instead of applying a statistical model to estimate the performance of the processor.
Original language | English (US) |
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Title of host publication | Proceedings - 9th International Symposium on High-Performance Computer Architecture, HPCA 2003 |
Publisher | IEEE Computer Society |
Pages | 281-291 |
Number of pages | 11 |
ISBN (Electronic) | 0769518710 |
DOIs | |
State | Published - 2003 |
Event | 9th IEEE International Symposium on High-Performance Computer Architecture, HPCA 2003 - Anaheim, United States Duration: Feb 8 2003 → Feb 12 2003 |
Publication series
Name | Proceedings - International Symposium on High-Performance Computer Architecture |
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Volume | 12 |
ISSN (Print) | 1530-0897 |
Other
Other | 9th IEEE International Symposium on High-Performance Computer Architecture, HPCA 2003 |
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Country/Territory | United States |
City | Anaheim |
Period | 2/8/03 → 2/12/03 |
Bibliographical note
Publisher Copyright:© 2003 IEEE.
Keywords
- Analytical models
- Application software
- Computational modeling
- Computer architecture
- Computer simulation
- Costs
- Performance analysis
- Space exploration
- Statistical analysis
- Time factors