The SPARC architecture manual (version 9)
The SPARC architecture manual (version 9)
The design and implementation of the 4.4BSD operating system
The design and implementation of the 4.4BSD operating system
Using the SimOS machine simulator to study complex computer systems
ACM Transactions on Modeling and Computer Simulation (TOMACS)
FLASH vs. (Simulated) FLASH: closing the simulation loop
ASPLOS IX Proceedings of the ninth international conference on Architectural support for programming languages and operating systems
Full-system timing-first simulation
SIGMETRICS '02 Proceedings of the 2002 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Measuring Experimental Error in Microprocessor Simulation
ISCA '01 Proceedings of the 28th annual international symposium on Computer architecture
Performance modeling and analysis of disk arrays
Performance modeling and analysis of disk arrays
lmbench: portable tools for performance analysis
ATEC '96 Proceedings of the 1996 annual conference on USENIX Annual Technical Conference
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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.