Pipeline gating: speculation control for energy reduction
Proceedings of the 25th annual international symposium on Computer architecture
Power aware microarchitecture resource scaling
Proceedings of the conference on Design, automation and test in Europe
Power-aware modulo scheduling for high-performance VLIW processors
ISLPED '01 Proceedings of the 2001 international symposium on Low power electronics and design
Automatically characterizing large scale program behavior
Proceedings of the 10th international conference on Architectural support for programming languages and operating systems
Basic Block Distribution Analysis to Find Periodic Behavior and Simulation Points in Applications
Proceedings of the 2001 International Conference on Parallel Architectures and Compilation Techniques
The design, implementation, and evaluation of a compiler algorithm for CPU energy reduction
PLDI '03 Proceedings of the ACM SIGPLAN 2003 conference on Programming language design and implementation
PowerScope: A Tool for Profiling the Energy Usage of Mobile Applications
WMCSA '99 Proceedings of the Second IEEE Workshop on Mobile Computer Systems and Applications
Combining Software and Hardware Monitoring for Improved Power and Performance Tuning
INTERACT '03 Proceedings of the Seventh Workshop on Interaction between Compilers and Computer Architectures
Characterizing and Predicting Program Behavior and its Variability
Proceedings of the 12th International Conference on Parallel Architectures and Compilation Techniques
Runtime Power Monitoring in High-End Processors: Methodology and Empirical Data
Proceedings of the 36th annual IEEE/ACM International Symposium on Microarchitecture
Proceedings of the 2004 international symposium on Low power electronics and design
ASPLOS XI Proceedings of the 11th international conference on Architectural support for programming languages and operating systems
Toward an Evaluation Infrastructure for Power and Energy Optimizations
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 11 - Volume 12
The Camino Compiler infrastructure
ACM SIGARCH Computer Architecture News - Special issue on the 2005 workshop on binary instrumentation and application
Motivation for Variable Length Intervals and Hierarchical Phase Behavior
ISPASS '05 Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2005
Fast, Accurate Microarchitecture Simulation Using Statistical Phase Detection
ISPASS '05 Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2005
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Fine-grained program power behavior is useful in both evaluating power optimizations and observing power optimization opportunities. Detailed power simulation is time consuming and often inaccurate. Physical power measurement is faster and objective. However, fine-grained measurement generates enormous amounts of data in which locating important features is difficult, while coarse-grained measurement sacrifices important detail. We present a program power behavior characterization infrastructure that identifies program phases, selects a representative interval of execution for each phase, and instruments the program to enable precise power measurement of these intervals to get their time-dependent power behavior. We show that the representative intervals accurately model the fine-grained time-dependent behavior of the program. They also accurately estimate the total energy of a program. Our compiler infrastructure allows for easy mapping between a measurement result and its corresponding source code. We improve the accuracy of our technique over previous work by using edge vectors , i.e., counts of traversals of control-flow edges, instead of basic block vectors, as well as incorporating event counters into our phase classification. We validate our infrastructure through the physical power measurement of 10 SPEC CPU 2000 integer benchmarks on an Intel Pentium 4 system. We show that using edge vectors reduces the error of estimating total program energy by 35% over using basic block vectors, and using edge vectors plus event counters reduces the error of estimating the fine-grained time-dependent power profile by 22% over using basic block vectors.