DAISY: dynamic compilation for 100% architectural compatibility
Proceedings of the 24th annual international symposium on Computer architecture
A scalable cross-platform infrastructure for application performance tuning using hardware counters
Proceedings of the 2000 ACM/IEEE conference on Supercomputing
Dynamic frequency and voltage control for a multiple clock domain microarchitecture
Proceedings of the 35th annual ACM/IEEE international symposium on Microarchitecture
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
Proceedings of the 36th annual IEEE/ACM International Symposium on Microarchitecture
Proceedings of the conference on Design, automation and test in Europe - Volume 1
Combining compiler and runtime IPC predictions to reduce energy in next generation architectures
Proceedings of the 1st conference on Computing frontiers
A Formal Approach to Frequent Energy Adaptations for Multimedia Applications
Proceedings of the 31st annual international symposium on Computer architecture
Pin: building customized program analysis tools with dynamic instrumentation
Proceedings of the 2005 ACM SIGPLAN conference on Programming language design and implementation
Power prediction for intel XScale® processors using performance monitoring unit events
ISLPED '05 Proceedings of the 2005 international symposium on Low power electronics and design
A Dynamic Compilation Framework for Controlling Microprocessor Energy and Performance
Proceedings of the 38th annual IEEE/ACM International Symposium on Microarchitecture
ISCA '08 Proceedings of the 35th Annual International Symposium on Computer Architecture
Comparing scalability prediction strategies on an SMP of CMPs
EuroPar'10 Proceedings of the 16th international Euro-Par conference on Parallel processing: Part I
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The importance and demand for various types of optimization techniques for program execution is growing rapidly. In particular, dynamic optimization techniques are regarded as important. Although conventional techniques usually generated an execution model for dynamic optimization by qualitatively analyzing the behaviors of computer systems in a knowledge-based manner, the proposed technique generates models by statistically analyzing the behaviors from quantitative data of hardware events. In the present paper, a novel dynamic voltage and frequency scaling (DVFS) method based on statistical analysis is proposed. The proposed technique is a hybrid technique in which static information, such as the breakpoint of program phases and, dynamic information, such as the number of cache misses given by the performance counter, are used together. Relationships between the performance and values of performance counters are learned statistically in advance. The compiler then inserts a run-time code for predicting the performance and setting the appropriate frequency/voltage depending on the predicted performance. The proposed technique can greatly reduce the energy consumption while satisfying soft timing constraints.