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SciSim: a software performance estimation framework using source code instrumentation
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Workshop on Software and Performance archive
Proceedings of the 7th international workshop on Software and performance table of contents
Princeton, NJ, USA
SESSION: Performance analysis from measurements table of contents
Pages 33-42  
Year of Publication: 2008
ISBN:978-1-59593-873-2
Authors
Zhonglei Wang  Teschnische Universität München, Munich, Germany
Antonio Sanchez  Teschnische Universität München, Munich, Germany
Andreas Herkersdorf  Teschnische Universität München, Munich, Germany
Sponsors
SIGSOFT: ACM Special Interest Group on Software Engineering
SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Recently, software performance estimation based on source code instrumentation shows promising results in the literature. It achieves significant speedup without compromising accuracy, compared with cycle-accurate simulations. However, much work still remains to be done to make this technique flexible and accurate enough to estimate software on complex processors. To the best of our knowledge, we are the first to propose ways to tackle microarchitecture related issues in the source code instrumentation approach. We perform static instruction scheduling for superscalar architectures at instrumentation time and combine instrumented code and microarchitecture simulators to model runtime interactions between software and microarchitecture. We have developed a new framework, SciSim, to provide a common infrastructure for the proposed approach. It is designed to be easily extendable and retargetable to different instruction set architectures and processors. Using SciSim SystemC modules may be automatically generated to integrate software into system-level simulation. We will present the applicability of SciSim in system-level design exploration of multiprocessor systems. At last, experiments with standard benchmarks are presented to validate the speed and accuracy of SciSim.


REFERENCES

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Collaborative Colleagues:
Zhonglei Wang: colleagues
Antonio Sanchez: colleagues
Andreas Herkersdorf: colleagues