Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 1 Energy Scale-Down in System Design: Optimizations for Reducing Power

July 3, 2003

Partha RanganathanE-scale project, HP Labs

Page 1

EnergyScale-down

Energy Scale-Down in System Design:

Optimizations for Reducing Power

Parthasarathy (Partha) Ranganathan

(with Bob Mayo)

Hewlett Packard Labs

July 3, 2003

July 3, 2003


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EnergyScale-down

Energy scale-down one component of broader power management work

This talk will focus on scale-down for mobile devices

Broader context

Power and energy management

Enterprise systems

Power costs & cooling

Mobile systems

Battery life

CPU display wireless

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EnergyScale-down Energy Scale-Down: Motivation

Mismatched system energy efficiency & desired functionality

• Tethered system (performance) hangover… – Increased performance at any cost, target worst-case benchmark

– Non-peak benchmarks consume more energy than needed

– Optimizations where energy costs outweigh small performance benefits

• User preference for convergence of diverse mobile devices– Combination of diff. needs => general-purpose designs (e.g.

phone/PDA) – Individual tasks consume more energy than needed

Do you need the full display to say three words: “you have mail”?

Do you need your wireless to respond within 100ms for email?

Do you need a 466 MHz processor for idle mode? for MS Word?

Solution: energy scale-down designSolution: energy scale-down designadaptivity to optimize energy efficiency based on task requirements

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EnergyScale-down Talk Roadmap

Motivation

Quantifying energy costs of inefficiencies

Scale-down optimizations to reduce energy

Display scale-down

Processor scale-down

Wireless scale-down

Ongoing work and summary

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EnergyScale-down

Quantifying Energy Costs of InefficienciesMismatched system energy efficiency and task functionality

What is the “optimal” energy needed for a task?

But, optimal energy consumption of task a challenging problem

– Past work “lower is better”, but no limits

– Hard-to-define target – fidelity, performance, costs, engineering

Our approach: use surrogate lower-bounds

– Special-purpose devices optimized for particular task

– Representative successful tradeoffs in functionality and battery-life

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EnergyScale-down Experimental methodology

Energy comparison for a spectrum of mobile devices– First such study to perform a consistent comparison

Devices:– Laptop (Armada M300), PDA (iPAQ 3630)– Cell phone (Nokia 8260), Pager (Blackberry W1000),

High-end MP3 (Nomad jukebox), low-end MP3 (ipaq PA1), voice-recorder (VoiceItVT90)

Benchmarks representative of typical mobile workloads

– Email, text messaging, phone calls, web browsing– MP3 play-back, text notes, audio notes, games, idle

mode– Benchmarks structured to have core functionality

consistent

Measurement – data acquisition of current/voltage– Total energy for task– Temporal power signatures

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EnergyScale-down

Results: Energy Comparison for Email

Email:• Laptop: 165X• Handheld: 15X• Cell phone: 6X• RIM pager: 92 mW

EnergyScale-down

Radio wakeup 100ms (iPAQ) 1.2 sec (cell) 5 sec (RIM)

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EnergyScale-down Overall results

Device Rcv Reply SpeakerHeadphone Text Audio Text AudioLaptop 15.16 W 16.25 W 18.02 W 15.99 W 16.55 W 14.20 W 14.65 W 14.40 W 15.50 W 13.975 WHandheld 1.386 W 1.439 W 2.091 W 1.700 W 1.742 W 1.276 W 1.557 W 1.319 W - 1.2584 WCellphone 539 mW 472 mW - - - - - 392 mW 1147 mW 26 mWEmail Pager 92 mW 72 mW - - - 78 mW - - - 13 mWHigh-end MP3 - - - 2.977 W - - - - - 1.884 WLow-end MP3 - - - 327 mW - - - - - 143 mWVoice Recorder - - - - - - 166 mW - - 17 mWvariance 16496% 22727% 861% 4890% 950% 18252% 8825% 3673% 1351% 107500%

MessagingIdle

Email MP3 Browse

Notes

Wide variation in power– 950% to 22,000% for similar task functions

– iPAQ 5X-10X higher energy

– Laptop 10X-100X higher energy

Variations related to better task-specific component matching

Significant potential from addressing energy inefficiencies

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EnergyScale-down Energy scale-down

Addressing general-purpose energy inefficiencies

Energy scale-downEnergy scale-down

Design and use adaptivity in hardware and software to scale-down energy based on task requirements

An informal taxonomy– Scale-down mechanism

– Gradation-based: same component, multiple modes– Examples : v/f scaling, gating, memory states, disk states, OLED-

based displays, protocol-level wireless optimizations, fidelity optimizations

– Plurality-based: “the kitchen-sink approach!”– Examples: hierarchy of displays, plurality networks, heterogeneous

chip multiprocessing

– Scale-down impact: user-directed versus user-transparent

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Motivation



Display scale-down


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EnergyScale-down Display scale-down [Mobisys2003]

Displays consume significant power in mobile systems

• 50% on laptops[7], 61% on handhelds[1]

Previous approaches:

• Turning off the entire display

• Using lower quality or smaller sized displays

Our approach: energy-adaptive display

• Power consumption based on content being displayed

– Understand user requirements

– Design and evaluate example

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EnergyScale-down Characterizing user requirements

User study: understand usage behavior of 17 Windows users

Display capacities are not fully utilized

• On average, ~60% of screen area used (window-of-focus)

– Even smaller for some users

• Other functions of display are not used always (color, res., …)

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EnergyScale-down

Display property vs. usage mismatches

Mismatches occur because of user/application-specific window usage

– Small: system-related messages and low-content windows

– Large: development, web, and emails

But display power is constant all the time

– Can we provide a means for energy to scale-down with lower usage?

Active area (window of focus) is 0-25% (23% of the samples)

20% Task Bar, 15% Program Manager, 5% Xterm, 60% misc windows


19% Xterm, 18% message composition, 6% Internet Explorer, 57% misc windows


33% Internet Explorer, 24% mail composition and reading, 57% misc windows


21% mail composition and reading, 20% Internet Explorer, 7% Excel, 52% misc windows

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EnergyScale-down Energy-adaptive display systems

Hardware support for power control at finer granularity

– Leverage emerging OLED technologies

– Pixel power based on pixel value (brightness, color)

– Currently in cell phones, expected in handhelds/laptops 2004-5

OLED market value ($ Millions) (all applications, world market, all drive types)

0

400

800

1200

1600

2000

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Mil

lio

ns o

f d

oll

ars

DigitalCamera&

Camcorders

3G Phones,Automotive

PDAs,Handhelds

Laptops

July 3, 2003


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EnergyScale-down

Energy-aware user interfacesSoftware support: energy-aware user interfaces (DarkWindows)

– Approximate user interest to window of focus

– Automatic power-aware adaptation of background brightness/color

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EnergyScale-down Evaluation methodology

Prototype user interface using VNC under Linux

OLED power model for representative user trace

Display Power = Pcontroller + Pdriver + Panel Power

Panel Power = Pixel Array Power

= ∑ Pred x pixelR + Pgreen x pixelG + Pblue x pixelB

Pred = 4.3 µW, Pgreen = 2.3 µW, Pblue = 4.3 µW

Xvnc

VNC Server VNC ViewerApplications

X protocol

TrackFocus

Window

Change pixel values in

framebufferOriginal Framebuffer

Modified Framebuffer

Xvnc VNC Viewer

VNC protocol

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EnergyScale-down Benefits from energy adaptivity

July 3, 2003


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EnergyScale-down Power savings

Power benefits from different interfaces– Benefits from both hardware and software

Broad acceptance of user interfaces in user study

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EnergyScale-down

Power savings: sensitivity experiments

Energy savings function of user preference

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EnergyScale-down

Other energy-adaptive designs

Hardware adaptability

• Emissive displays

• Hybrid technologies

• Multi-display configuration

• Other output modes

Software adaptability

• “Flashlight” or “headlight” cursor

• “Sticky lamps” on desktop

• Application-specific dimming

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EnergyScale-down

Display scale-down: Summary

Display component a large fraction of total power

First detailed user study on screen usage behavior

– Only fraction of screen area used

– Many properties of display (color, resolution) often not used

Energy-adaptive display design

– Hardware support for fine-grained power control

– Software support for energy-aware user interfaces

– Significant power benefits with low user intrusiveness

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Motivation



Display scale-down



July 3, 2003


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EnergyScale-down Processor Scale-down [MICRO2003]

Motivation: CPU power important component of total power

Previous approaches– Voltage and frequency scaling limited by feature size– Architectural adaptation limited to dynamic power

Our Solution: Heterogeneous Multi-core Single-ISA Our Solution: Heterogeneous Multi-core Single-ISA ArchitectureArchitecture• Have multiple heterogeneous cores on the same die• Match workload to core with best energy efficiency• Power down the unused cores

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EnergyScale-down Characterizing workload behavior

Methodology

– Simulation study of 14 SPEC2000 benchmarks

– Five-core CPU (MIPS R4K, EV4, EV5, EV6, EV8-)

Mismatch between energy efficiency and workload requirement

Core difference varies based on workload or workload phases (IPS)

Varying core energy efficiencies for the same workload (IPS/W)

0

1.8

1 Program execution

IPS

R4700 EV4 EV5 EV6 EV8-

0

3.5

1

Program execution

IPS

/W

R4700 EV4 EV5 EV6 EV8-

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EnergyScale-down

Power benefits

0

1.8

1

Program execution

IPS

R4700 EV4 EV5 EV6 EV8- Best-path

Oracle-choose best energy efficiency

– 39% average energy savings with 3% performance loss

– 2X-4X benefits in half the benchmarks

Oracle-choose best energy-delay– 75% average energy savings

with 24% performance loss– 2X-11X benefits in all

benchmarks– Significantly better than

voltage/frequency scaling

Realistic heuristics– within 90% of oracle switching

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EnergyScale-down CPU scale-down: Summary

Using scale-down to address processor power

Simulation study characterizing energy efficiency mismatch

Heterogeneous single-ISA CMP architecture• Significant power benefits• Better than voltage/frequency scaling

Ongoing work• Other heuristics• Other architectures

– Less diversity, energy-accentuated diversity

• Implications on performance– Area vs. throughput

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Motivation



Display scale-down


Other work and summary

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EnergyScale-down Other work: Wireless scale-down

Motivation: wireless component of power– Many workloads spend most power “listening”

– E.g., email, phone calls, SMS messages, conferencing– Idle power 89% of total wireless power

Our approach: scale-down for idle-mode power management– Expose application requirements to physical layer– Change “listen interval” parameters for 802.11

Power benefits– Changing power interval to 1sec: 20% power benefits– Changing listen interval to 1min: 90% power benefits

Listen Interval

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EnergyScale-down Other work: Enterprise scale-down

Energy scale-downEnergy scale-downadaptivity to optimize energy efficiency based on task requirements

Inefficiencies from designing for peak-performance needsInefficiencies from designing for peak-tolerance needsInefficiencies from aggregation of componentsInefficiencies from modularity of functionsInefficiencies from not addressing total costs of ownershipInefficiencies from inadequate automation

Preliminary results promising

Operations

Power delivery

Computation workloads, resources, goodness attributes

Heat cooling

Electricity Heat

Human effort

OperationsOperations

Power deliveryPower delivery

Computation workloads, resources, goodness attributes

Heat coolingHeat cooling

Electricity Heat

Human effort

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EnergyScale-down Summary

Energy and power important considerations for future systems– Significant mismatches in energy efficiency and task functions

Quantification energy costs of inefficiencies– First study to perform consistent comparison of spectrum of devices

– Special-purpose devices 5X-100X better than general-purpose devices– Good surrogate-bounds and best-practices for energy optimizations

Scale-down: adaptivity to optimize efficiency based on requirements

– Energy-adaptive displays: energy benefits with acceptable user interfaces

– Heterogeneous CMPs: energy benefits with acceptable performance

– Wireless scale-down: energy benefits with acceptable response delays

Critical to integrate energy scale-down in future designs

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EnergyScale-down More information

Relevant Papers– Energy consumption in mobile systems: why future systems

need requirements-aware energy scale-down, Mayo and Ranganathan, HP Tech report, HPL TR2003-167 [Under review, IEEE Computer]

– Energy-adaptive display system designs for future mobile environments, Iyer, Luo, Mayo and Ranganathan, Mobisys 2003

– Single-ISA Heterogeneous Multi-Core Architectures: The Potential for Power Reduction, Kumar, Farkas, Jouppi, Ranganathan, Tullsen, MICRO 2003, CAL2003

– Idle-Mode Power Management for Personal Wireless Devices, Abou-ghazala, Mayo and Ranganathan, HP Technical report HPL2003-102

Contact– http://web.hpl.hp.com/reserach/lss/projects/smartpower/

– Email: [email protected]

Documents

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 1 Energy Scale-Down in System Design: Optimizations for Reducing Power