DMCA
Modeling Superscalar Processors via Statistical Simulation (2001)
| Venue: | in International Conference on Parallel Architectures and Compilation Techniques |
| Citations: | 107 - 4 self |
BibTeX
@INPROCEEDINGS{Nussbaum01modelingsuperscalar,
author = {Sébastien Nussbaum and James E. Smith},
title = {Modeling Superscalar Processors via Statistical Simulation},
booktitle = {in International Conference on Parallel Architectures and Compilation Techniques},
year = {2001},
pages = {15--24}
}
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Abstract
Statistical simulation is a technique for fast performance evaluation of superscalar processors. First, intrinsic statistical information is collected from a single detailed simulation of a program. This information is then used to generate a synthetic instruction trace that is fed to a simple processor model, along with cache and branch prediction statistics. Because of the probabilistic nature of the simulation, it quickly converges to a performance rate. The simplicity and simulation speed make it useful for fast design space exploration; as such, it is a good complement to conventional detailed simulation.
Keyphrases
statistical simulation superscalar processor performance rate intrinsic statistical information synthetic instruction trace simulation speed good complement conventional detailed simulation fast performance evaluation branch prediction statistic simple processor model fast design space exploration single detailed simulation probabilistic nature
