Name
Abstract | ||
|---|---|---|
Execution-driven simulation has become the primary method for evaluating architectural techniques as it facilitates rapid design space exploration without the cost of building prototype hardware. To date, most simulation systems have either focused on the cycle-accurate modeling of user-level code while ignoring operating system and I/O effects, or have modeled complete systems while abstracting away many cycle-accurate timing details. The ML-RSIM simulation system presented here combines detailed hardware models with the ability to simulate user-level as well as operating system activity, making it particularly suitable for exploring the interaction of applications with the operating system and I/O activity. This paper provides an overview of the design of the simulation infrastructure and discusses its strengths and weaknesses in terms of accuracy, flexibility, and performance. A validation study using LM Bench microbenchmarks shows a good correlation for most of the architectural characteristics, while operating system effects show a larger variability. By quantifying the accuracy of the simulation tool in various areas, the validation effort not only helps gauge the validity of simulation results but also allows users to assess the suitability of the tool for a particular purpose. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1016/j.sysarc.2005.07.001 | Journal of Systems Architecture |
Keywords | Field | DocType |
simulation infrastructure,simulation tool,system activity,operating system,ml-rsim simulation system,simulation result,ml-rsim system simulator,system effect,simulator accuracy,simulator validation,execution-driven simulator,complete system,simulation system,execution-driven simulation | Computer architecture simulator,Simulation system,Computer science,Simulation,Real-time computing,Design space exploration,Strengths and weaknesses | Journal |
Volume | Issue | ISSN |
52 | 5 | Journal of Systems Architecture |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lambert Schaelicke | 1 | 279 | 20.23 |
| Mike Parker | 2 | 0 | 0.34 |