Energy
Scale-down
Energy Scale-Down in System
Design:
Optimizations for Reducing Power
Parthasarathy (Partha) Ranganathan
(with Bob Mayo)
Hewlett Packard Labs
July 3, 2003
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 1
Energy
Scale-down
Broader context
Energy scale-down one component of broader power
management work
Power and energy management
Enterprise systems
Mobile systems
Power costs & cooling
Battery life
CPU
display
wireless
This talk will focus on scale-down for mobile devices
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 2
Energy
Scale-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 design
adaptivity to optimize energy efficiency based on task requirements
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 3
Energy
Scale-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
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 4
Energy
Scale-down
Quantifying Energy Costs of
Inefficiencies
Mismatched 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 batterylife
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 5
Energy
Scale-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
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 6
Energy
Scale-down
Results: Energy Comparison for Email
Radio wakeup
100ms (iPAQ)
1.2 sec (cell)
5 sec (RIM)
Email:
• Laptop: 165X
• Handheld: 15X
• Cell phone: 6X
• RIM pager: 92 mW
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 7
Energy
Scale-down
Overall results
Email
MP3
Device
Rcv
Reply SpeakerHeadphone Browse
Laptop
15.16 W 16.25 W 18.02 W
15.99 W 16.55 W
Handheld
1.386 W 1.439 W 2.091 W
1.700 W 1.742 W
Cellphone 539 mW 472 mW
Email Pager 92 mW 72 mW
High-end MP3
2.977 W
Low-end MP3
327 mW
Voice Recorder
variance
16496% 22727%
861%
4890% 950%
Notes
Messaging
Text
Audio Text
Audio
14.20 W 14.65 W 14.40 W 15.50 W
1.276 W 1.557 W 1.319 W
- 392 mW1147 mW
78 mW
- 166 mW
18252% 8825% 3673% 1351%
Idle
13.975 W
1.2584 W
26 mW
13 mW
1.884 W
143 mW
17 mW
107500%
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
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 8
Energy
Scale-down
Energy scale-down
Addressing general-purpose energy inefficiencies
Energy 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
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 9
Energy
Scale-down
Talk Roadmap
Motivation
Quantifying energy costs of inefficiencies
Scale-down optimizations to reduce energy
Display scale-down
Ongoing work and summary
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 10
Energy
Scale-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
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 11
Energy
Scale-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., …)
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 12
Energy
Scale-down
Display property vs. usage mismatches
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
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 withPartha
lower
usage?
Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 13
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)
2000
1600
Millions of dollars
Energy
Scale-down
1200
Laptops
800
PDAs,
Handhelds
3G Phones,
Automotive
400
Digital
Camera&
Camcorders
0
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 14
Energy
Scale-down
Energy-aware user interfaces
Software support: energy-aware user interfaces (DarkWindows)
– Approximate user interest to window of focus
– Automatic power-aware adaptation of background brightness/color
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 15
Energy
Scale-down
Evaluation methodology
Prototype user interface using VNC under Linux
Xvnc
X protocol
Applications
VNC Server
Xvnc
Original
Framebuffer
Track
Focus
Window
VNC protocol
VNC Viewer
Change pixel
values in
framebuffer
Modified
Framebuffer
VNC Viewer
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
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 16
Energy
Scale-down
Benefits from energy adaptivity
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 17
Energy
Scale-down
Power savings
Power benefits from different interfaces
– Benefits from both hardware and software
Broad acceptance of user interfaces in user study
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 18
Energy
Scale-down
Power savings: sensitivity experiments
Energy savings function of user preference
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 19
Energy
Scale-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
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 20
Energy
Scale-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
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 21
Energy
Scale-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
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 22
Energy
Scale-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
Architecture
• Have multiple heterogeneous cores on the same die
• Match workload to core with best energy efficiency
• Power down the unused cores
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 23
Energy
Scale-down
Characterizing workload behavior
R4700
EV4
EV5
EV6
1.8
R4700
EV4
EV5
EV6
EV8-
IPS/W
3.5
IPS
0
EV8-
1
Program execution
0
1
Program execution
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)
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 24
Power benefits
Oracle-choose best energy
efficiency
– 39% average energy savings with
3% performance loss
– 2X-4X benefits in half the
benchmarks
R4700
EV4
EV5
EV6
EV8-
Best-path
1.8
IPS
Energy
Scale-down
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
0
1
Program execution
Realistic heuristics
– within 90% of oracle switching
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 25
Energy
Scale-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
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 26
Energy
Scale-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
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 27
Energy
Scale-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
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 28
Energy
Scale-down
Other work: Enterprise scale-down
Electricity
Power
delivery
Computation
Heat
workloads, resources,
goodness attributes
Heat
cooling
Human effort
Operations
Energy scale-down
adaptivity to optimize energy efficiency based on task requirements
Inefficiencies from designing for peak-performance needs
Inefficiencies from designing for peak-tolerance needs
Inefficiencies from aggregation of components
Inefficiencies from modularity of functions
Inefficiencies from not addressing total costs of ownership
Inefficiencies from inadequate automation
Preliminary results promising
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 29
Energy
Scale-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
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 30
Energy
Scale-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, Aboughazala, Mayo and Ranganathan, HP Technical report HPL2003-102
Contact
– http://web.hpl.hp.com/reserach/lss/projects/smartpower/
– Email: partha.ranganathan@hp.com
Partha Ranganathan
E-scale project, HP Labs
July 3, 2003
Page 31