Pentium 4 Performance-Monitoring Features
IEEE Micro
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
The Danger of Interval-Based Power Efficiency Metrics: When Worst Is Best
IEEE Computer Architecture Letters
Proceedings of the 39th Annual IEEE/ACM International Symposium on Microarchitecture
An efficient frequency scaling approach for energy-aware embedded real-time systems
ARCS'05 Proceedings of the 18th international conference on Architecture of Computing Systems conference on Systems Aspects in Organic and Pervasive Computing
Power and energy-aware processor scheduling
Proceedings of the 2nd ACM/SPEC International Conference on Performance engineering
Predicting Performance Impact of DVFS for Realistic Memory Systems
MICRO-45 Proceedings of the 2012 45th Annual IEEE/ACM International Symposium on Microarchitecture
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In this paper, a runtime performance projection model for dynamic power management is proposed. The model is built as a first-order linear equation using a linear regression model. It could be used to estimate performance impact from different p-states (voltage-frequency pairs). Workload behavior is monitored dynamically for a program region of 100M instructions using hardware performance monitoring counters (PMCs), and performance for the next region is estimated using the proposed model. For each 100Minstructions interval, the performance of all processor p-states is estimated and the lowest frequency is selected within specified performance constraints. The selected frequency is set with a low-overhead DVFS-based (dynamic voltagefrequency scaling) p-state changing mechanism for the next program region. We evaluate the performance degradation and the amount of energy saving of our dynamic power management scheme using the proposed projection model for SPEC CPU2000 benchmark on a Pentium M platform. We measure the execution time and energy consumption for 4 specified constraints - 10%, 20%, 40%, 80%, on the maximum allowed performance degradation. The result shows that our dynamic management scheme saves energy consumption by 3%, 18%, 38% and 48% with a performance degradation of 3%, 19%, 45% and 79% under 10%,20%,40% and 80% constraints, respectively.