The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
Trace-driven modeling and analysis of CPU scheduling in a multiprogramming system
Communications of the ACM
Performance monitoring in a time-sharing system
Communications of the ACM
Computer system simulation with ASPOL
ANSS '73 Proceedings of the 1st symposium on Simulation of computer systems
Describing program behavior in a multiprogramming computer system
ANSS '75 Proceedings of the 3rd symposium on Simulation of computer systems
Process and event control in ASPOL
ANSS '75 Proceedings of the 3rd symposium on Simulation of computer systems
Gathering and analyzing data from a computer system: A case study
ACM '75 Proceedings of the 1975 annual conference
Simulation of computer systems using automatically generated load descriptions
WSC '74 Proceedings of the 7th conference on Winter simulation - Volume 2
Design of a Computer—The Control Data 6600
Design of a Computer—The Control Data 6600
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This paper compares the efficiency of trace-driven simulation models of computer systems with the efficiency of function driven models. In a trace-driven model (TDM), the next service request for a task is selected from a file of requests which was created earlier, often from data derived from a functioning system. This can be compared to a function-driven model (FDM), in which the next service request is selected using generation techniques based on random deviates. While both kinds of models can produce statistically accurate results, a TDM is thought to be inherently more accurate, but it has been suspected that a FDM is faster. The comparison of these two techniques is based on a simulation model of a computer system which has been specially constructed so as to operate either as a TDM or an FDM. The key feature of the study is that by using this model, we have isolated the demand-generation technique (either trace-driven or function-driven) as the single factor affecting performance of the model. A run-time program monitor and a software-monitor event probe are used to evaluate the resources used by various runs of the two kinds of simulation models. The results indicate that, contrary to earlier expectations, the performance of both techniques is comparable. We also demonstrate the effects of various block sizes on the performance of the TDM and the effects of the complexity of the request functions on the performance of the FDM.