DocumentCode :
3307041
Title :
Phase characterization for power: evaluating control-flow-based and event-counter-based techniques
Author :
Isci, Canturk ; Martonosi, Margaret
Author_Institution :
Dept. of Electr. Eng., Princeton Univ., NJ, USA
fYear :
2006
fDate :
11-15 Feb. 2006
Firstpage :
121
Lastpage :
132
Abstract :
Computer systems increasingly rely on dynamic, phase-based system management techniques, in which system hardware and software parameters may be altered or tuned at runtime for different program phases. Prior research has considered a range of possible phase analysis techniques, but has focused almost exclusively on performance-oriented phases; the notion of power-oriented phases has not been explored. Moreover, the bulk of phase-analysis studies have focused on simulation evaluation. There is need for real-system experiments that provide direct comparison of different practical techniques (such as control flow sampling, event counters, and power measurements) for gauging phase behavior. In this paper, we propose and evaluate a live, real-system measurement framework for collecting and analyzing power phases in running applications. Our experimental frameworks simultaneously collects control flow, performance counter and live power measurement information. Using this framework, we directly compare between code-oriented techniques (such as "basic block vectors") and performance counter techniques for characterizing power phases. Across a collection of both SPEC2000 benchmarks as well as mainstream desktop applications, our results indicate that both techniques are promising, but that performance counters consistently provide better representation of power behavior. For many of the experimented cases, basic block vectors demonstrate a strong relationship between the execution path and power consumption. However, there are instances where power behavior cannot be captured from control flow, for example due to differences in memory hierarchy performance. We demonstrate these with examples from real applications. Overall, counter-based techniques offer average classification errors of 1.9% for SPEC and 7.1% for other benchmarks, while basic block vectors achieve 2.9% average errors for SPEC and 11.7% for other benchmarks respectively.
Keywords :
benchmark testing; computer architecture; performance evaluation; power consumption; SPEC2000 benchmark; basic block vector; code-oriented technique; control-flow sampling; event counter; mainstream desktop application; performance counter; power consumption; power phase characterization; real-system power measurement; Counting circuits; Energy consumption; Hardware; Performance analysis; Phase measurement; Power measurement; Power system management; Runtime; Sampling methods; Software systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
High-Performance Computer Architecture, 2006. The Twelfth International Symposium on
ISSN :
1530-0897
Print_ISBN :
0-7803-9368-6
Type :
conf
DOI :
10.1109/HPCA.2006.1598119
Filename :
1598119
Link To Document :
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