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Transcript of Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 1 Energy Scale-Down...
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
Partha RanganathanE-scale project, HP Labs
Page 2
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
July 3, 2003
Partha RanganathanE-scale project, HP Labs
Page 3
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
July 3, 2003
Partha RanganathanE-scale project, HP Labs
Page 4
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
July 3, 2003
Partha RanganathanE-scale project, HP Labs
Page 5
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
July 3, 2003
Partha RanganathanE-scale project, HP Labs
Page 6
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
July 3, 2003
Partha RanganathanE-scale project, HP Labs
Page 7
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)
July 3, 2003
Partha RanganathanE-scale project, HP Labs
Page 8
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
July 3, 2003
Partha RanganathanE-scale project, HP Labs
Page 9
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
July 3, 2003
Partha RanganathanE-scale project, HP Labs
Page 10
EnergyScale-down Talk Roadmap
Motivation
Quantifying energy costs of inefficiencies
Scale-down optimizations to reduce energy
Display scale-down
Ongoing work and summary
July 3, 2003
Partha RanganathanE-scale project, HP Labs
Page 11
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
July 3, 2003
Partha RanganathanE-scale project, HP Labs
Page 12
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., …)
July 3, 2003
Partha RanganathanE-scale project, HP Labs
Page 13
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
Active area (window of focus) is 25-50% (22% of the samples)
19% Xterm, 18% message composition, 6% Internet Explorer, 57% misc windows
Active area (window of focus) is 50-75% (28% of the samples)
33% Internet Explorer, 24% mail composition and reading, 57% misc windows
Active area (window of focus) is 75-100% (27% of the samples)
21% mail composition and reading, 20% Internet Explorer, 7% Excel, 52% misc windows
July 3, 2003
Partha RanganathanE-scale project, HP Labs
Page 14
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
Partha RanganathanE-scale project, HP Labs
Page 15
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
July 3, 2003
Partha RanganathanE-scale project, HP Labs
Page 16
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
July 3, 2003
Partha RanganathanE-scale project, HP Labs
Page 17
EnergyScale-down Benefits from energy adaptivity
July 3, 2003
Partha RanganathanE-scale project, HP Labs
Page 18
EnergyScale-down Power savings
Power benefits from different interfaces– Benefits from both hardware and software
Broad acceptance of user interfaces in user study
July 3, 2003
Partha RanganathanE-scale project, HP Labs
Page 19
EnergyScale-down
Power savings: sensitivity experiments
Energy savings function of user preference
July 3, 2003
Partha RanganathanE-scale project, HP Labs
Page 20
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
July 3, 2003
Partha RanganathanE-scale project, HP Labs
Page 21
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
July 3, 2003
Partha RanganathanE-scale project, HP Labs
Page 22
EnergyScale-down Talk Roadmap
Motivation
Quantifying energy costs of inefficiencies
Scale-down optimizations to reduce energy
Display scale-down
Processor scale-down
Ongoing work and summary
July 3, 2003
Partha RanganathanE-scale project, HP Labs
Page 23
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
July 3, 2003
Partha RanganathanE-scale project, HP Labs
Page 24
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-
July 3, 2003
Partha RanganathanE-scale project, HP Labs
Page 25
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
July 3, 2003
Partha RanganathanE-scale project, HP Labs
Page 26
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
July 3, 2003
Partha RanganathanE-scale project, HP Labs
Page 27
EnergyScale-down Talk Roadmap
Motivation
Quantifying energy costs of inefficiencies
Scale-down optimizations to reduce energy
Display scale-down
Processor scale-down
Other work and summary
July 3, 2003
Partha RanganathanE-scale project, HP Labs
Page 28
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
July 3, 2003
Partha RanganathanE-scale project, HP Labs
Page 29
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
July 3, 2003
Partha RanganathanE-scale project, HP Labs
Page 30
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
July 3, 2003
Partha RanganathanE-scale project, HP Labs
Page 31
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]