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Issue No.02 - Feb. (2013 vol.62)
pp: 376-389
Dehao Chen , Google Inc, Mountain View
Neil Vachharajani , Pure Storage Inc, Mountain View
Robert Hundt , Google Inc, Mountain View
Xinliang Li , Google Inc, Mountain View
Stephane Eranian , Google Inc, Mountain View
Wenguang Chen , Tsinghua University, Beijing
Weimin Zheng , Tsinghua University, Beijing
Feedback-directed optimization (FDO) is effective in improving application runtime performance, but has not been widely adopted due to the tedious dual-compilation model, the difficulties in generating representative training data sets, and the high runtime overhead of profile collection. The use of hardware-event sampling overcomes these drawbacks by providing a lightweight approach to collect execution profiles in the production environment, which naturally consumes representative input. Yet, hardware event samples are typically not precise at the instruction or basic-block granularity. These inaccuracies lead to missed performance when compared to instrumentation-based FDO. In this paper, we use Performance Monitoring Unit (PMU)-based sampling to collect the instruction frequency profiles. By collecting profiles using multiple events, and applying heuristics to predict the accuracy, we improve the accuracy of the profile. We also show how emerging techniques can be used to further improve the accuracy of the sample-based profile. Additionally, these emerging techniques are used to collect value profiles, as well as to assist a lightweight interprocedural optimizer. All these profiles are represented in a portable form, thus they can be used across different platforms. We demonstrate that sampling-based FDO can achieve an average of 92 percent of the performance gains obtained using instrumentation-based exact profiles for both SPEC CINT2000 and CINT2006 benchmarks. The overhead of collection is only 0.93 percent on average, while compiler-based instrumentation incurs 2.0-351.5 percent overhead (and 10x overhead on an industrial web search application).
Instruments, Radiation detectors, Optimization, Hardware, Phasor measurement units, Monitoring, Program processors, last branch record, Sample profile, feedback directed optimization, performance counter
Dehao Chen, Neil Vachharajani, Robert Hundt, Xinliang Li, Stephane Eranian, Wenguang Chen, Weimin Zheng, "Taming Hardware Event Samples for Precise and Versatile Feedback Directed Optimizations", IEEE Transactions on Computers, vol.62, no. 2, pp. 376-389, Feb. 2013, doi:10.1109/TC.2011.233
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