Modeling Superscalar Processors via Statistical Simulation (2001)
| Venue: | in International Conference on Parallel Architectures and Compilation Techniques |
| Citations: | 93 - 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.
