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Finding Extreme Behaviors in Microprocessor Workloads

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Transactions on High-Performance Embedded Architectures and Compilers IV

Part of the book series: Lecture Notes in Computer Science ((THIPEAC,volume 6760))

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Abstract

Power consumption has emerged as a key design concern across the entire computing range, from low-end embedded systems to high-end supercomputers. Understanding the power characteristics of a microprocessor under design requires a careful study using a variety of workloads. These workloads range from benchmarks that represent typical behavior up to hand-tuned stress benchmarks (so called stressmarks) that stress the microprocessor to its extreme power consumption.

This paper closes the gap between these two extremes by studying techniques for the automated identification of stress patterns (worst-case or extreme application behaviors) in typical workloads. For doing so, we borrow from sampled simulation theory and we provide two key insights. First, although representative sampling is slightly less effective in characterizing average behavior than statistical sampling, it is substantially more effective in finding stress patterns. Second, we find that threshold clustering is a better alternative than k-means clustering, which is typically used in representative sampling, for finding stress patterns. We identify a wide range of extreme behaviors, such as max energy, max power, max CPI, max branch misprediction rate, and max cache miss rate stress patterns. Overall, we can identify extreme behaviors in microprocessor workloads with a three orders of magnitude speedup and an error of a few percent on average.

Lieven Eeckhout is a postdoctoral fellow with the Fund for Scientific Research in Flanders (Belgium) (FWO-Vlaanderen). Additional support is provided by the FWO projects G.0232.06 and G.0255.08, and the UGent-BOF project 01J14407.

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Authors and Affiliations

  1. ELIS Department, Ghent University, Belgium

    Frederik Vandeputte & Lieven Eeckhout

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  1. Frederik Vandeputte
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  2. Lieven Eeckhout
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  1. Department of Computer Science and Engineering, Chalmers University of Technology, 412 96, Gothenburg, Sweden

    Per Stenström

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Vandeputte, F., Eeckhout, L. (2011). Finding Extreme Behaviors in Microprocessor Workloads. In: Stenström, P. (eds) Transactions on High-Performance Embedded Architectures and Compilers IV. Lecture Notes in Computer Science, vol 6760. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24568-8_8

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  • DOI: https://doi.org/10.1007/978-3-642-24568-8_8

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