Enhancing network processor simulation speed with statistical input sampling

Authors:
Jia Yu;Jun Yang;Shaojie Chen;Yan Luo;Laxmi Bhuyan
Affiliations:
Department of Computer Science and Engineering;Department of Computer Science and Engineering;Department of Statistics, University of California, Riverside;Department of Computer Science and Engineering;Department of Computer Science and Engineering
Venue:
HiPEAC'05 Proceedings of the First international conference on High Performance Embedded Architectures and Compilers
Year:
2005

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Abstract

While cycle-accurate simulation tools have been widely used in modeling high-performance processors, such an approach can be hindered by the increasing complexity of the simulation, especially in modeling chip multi-proce- ssors with multi-threading such as the network processors (NP). We have observed that for NP cycle level simulation, several days of simulation time covers only about one second of the real-world network traffic. Existing approaches to accelerating simulation are through either code analysis or execution sampling. Unfortunately, they are not applicable in speeding up NP simulations due to the small code size and the iterative nature of NP applications. We propose to sample the traffic input to the NP so that a long packet trace is represented by a much shorter one with simulation error bounded within ±3% and 95% confidence. Our method resulted one order of magnitude improvement in the NP simulation speed.