Paper Info
Title
A superscalar simulation employing poisson distributed stalls
Abstract
This paper presents a statistical approach to estimating the performance of a superscalar processor. Traditional trace-driven simulators can take a large amount time to conduct a performance evaluation of a machine, especially as the number of instructions increases. The result of this type of simulation is typically tied to the particular trace that was run. Elements such as dependencies, delays, and stalls are all a direct result of the particular trace being run, and can differ from trace to trace. This paper describes a model designed to separate simulation results from a specific trace. Rather than running a trace-driven simulation, a statistical model is employed, more specifically a Poisson distribution, to predict how these types of delay affects performance. Through the use of this statistical model, a performance evaluation can be conducted using a general code model, with specific stall rates, rather than a particular code trace. This model allows simulations to quickly run tens of millions of instructions and evaluate the performance of a particular micro-architecture while at the same time, allowing the flexibility to change the structure of the architecture.
Year
DOI
Venue
2008
10.1016/j.compeleceng.2007.03.003
Computers & Electrical Engineering
Keywords
Field
DocType
statistical approach,general code model,particular micro-architecture,particular trace,particular code trace,trace-driven simulation,statistical model,simulation result,specific trace,performance evaluation,superscalar simulation,poisson distribution
Architecture,Computer science,Stall (fluid mechanics),Parallel computing,Real-time computing,Statistical model,Poisson distribution,Superscalar
Journal
Volume
Issue
ISSN
34
3
Computers and Electrical Engineering
Citations 
PageRank 
References 
0
0.34
18
Authors
3
Name
Order
Citations
PageRank
Christopher B. Smith1172.77
David R. Mandel211.40
Eugene John32516.99