Chia-Yen HsiehChia-Yen Hsieh

Laboratory for Reliable Computing

Microarchitecture-Level PoMicroarchitecture-Level Power Managementwer Management

Iyer, A. Marculescu, D., Member, IEEE IEEE Transaction on VLSI System, June

2002

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OutlineOutline

Introduction

Hotspot detection

Energy optimal configuration

Implement

Result

Conclusion

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Low Power Issue Low Power Issue

Market for mobile and embedded systems is expanding at a rapid rate, battery life is important

System-level power management Memory and cache power optimization Low-power sleep mode Dynamic supply voltage variation

Microarchitecture-level Trade-off between energy and performance Execution application program for low power usi

ng profiling

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Execution ProfileExecution Profile

Wide variation in resource usage from one section of an application’s code to another Execution profile of epic benchmark

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Energy Variation Energy Variation

The quantity and organization of the processor’s resources will affect the overall execution profile and the energy consumption Energy variation of lisp benchmark

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Motivation Motivation

Low-end configuration consume higher power Higher CPI

High-end configuration consume higher power Resource usage Power of unused module

Identify the right configuration for each code region in terms of various processor resources

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Basic Block and HotspotBasic Block and Hotspot

Basic block branch

Hotspots collection of basic blocks frequently execution

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Hotspot Detection HardwareHotspot Detection Hardware

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Execution Time Spent in HotspotsExecution Time Spent in Hotspots

Optimal configuration for that hotspots

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Energy-Optimal ConfigurationEnergy-Optimal Configuration

Configuration : combination of several processor parameters under control

Optimum configuration : least energy dissipation per committed instruction

Determine approximate energy dissipation

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Energy-Optimal ConfigurationEnergy-Optimal Configuration

Run 14 benchmarks Energy consumption > 70%

Relative pre-access energy consumption on hottest parts of the simplescalar processor model

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Power-Profiling HardwarePower-Profiling Hardware

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Optimal the ConfigurationOptimal the Configuration

Hotspots is detected

Estimate power dissipation for all possible configurations

Optimal configuration of the processor for current hotspot is determined

Processor is switched to optimal configuration for the whole duration of the hotspots

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ExperimentsExperiments

Baseline configuration used

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Processor Model with Profiling Processor Model with Profiling HardwareHardware

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Power Variation Power Variation

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Energy VariationEnergy Variation

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Instruction Window Energy VariationInstruction Window Energy Variation

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Performance Variation Performance Variation

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Result Result

Saving obtained using run-time resource scaling

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Conclusion Conclusion

Major execution time of most applications is spent inside hotspots Detect hotspots Optimize the processor’s energy consumption

inside hotspots Increase in energy-efficient of the machine

Saving more power and energy with less performance penalty