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 Parthasarathy (Partha) Ranganathan (with Bob Mayo) Hewlett Packard Labs July 3, 2003

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 2 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

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 3 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 ? 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

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 4 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

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 5 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 battery- life

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 6 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 – , 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

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 7 Results: Energy Comparison for Laptop: 165X Handheld: 15X Cell phone: 6X RIM pager: 92 mW Energy Scale-down Radio wakeup 100ms (iPAQ) 1.2 sec (cell) 5 sec (RIM)

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 8 Overall results 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

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 9 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

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 10 Talk Roadmap Motivation Quantifying energy costs of inefficiencies Scale-down optimizations to reduce energy Display scale-down Ongoing work and summary

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 11 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

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 12 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., …)

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 13 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 s 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 % (27% of the samples) 21% mail composition and reading, 20% Internet Explorer, 7% Excel, 52% misc windows

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 14 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 Digital Camera& Camcorders 3G Phones, Automotive PDAs, Handhelds Laptops

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 15 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

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 16 Evaluation methodology Prototype user interface using VNC under Linux OLED power model for representative user trace Display Power = P controller + P driver + Panel Power Panel Power = Pixel Array Power = ∑ P red x pixel R + P green x pixel G + P blue x pixel B P red = 4.3 µW,P green = 2.3 µW, P blue = 4.3 µW Xvnc VNC ServerVNC Viewer Applications X protocol Track Focus Window Change pixel values in framebuffer Original Framebuffer Modified Framebuffer XvncVNC Viewer VNC protocol

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 17 Benefits from energy adaptivity

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 18 Power savings Power benefits from different interfaces –Benefits from both hardware and software Broad acceptance of user interfaces in user study

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 19 Power savings: sensitivity experiments Energy savings function of user preference

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 20 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

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 21 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

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 22 Talk Roadmap Motivation Quantifying energy costs of inefficiencies Scale-down optimizations to reduce energy Display scale-down Processor scale-down Ongoing work and summary

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 23 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

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 24 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)

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 25 Power benefits 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

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 26 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

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 27 Talk Roadmap Motivation Quantifying energy costs of inefficiencies Scale-down optimizations to reduce energy Display scale-down Processor scale-down Other work and summary

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 28 Other work: Wireless scale-down Motivation: wireless component of power –Many workloads spend most power “listening” –E.g., , 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 Power benefits –Changing power interval to 1sec: 20% power benefits –Changing listen interval to 1min: 90% power benefits Listen Interval

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 29 Other work: Enterprise scale-down 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

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 30 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

Energy Scale-down July 3, 2003 Partha Ranganathan E-scale project, HP Labs Page 31 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 TR [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 HPL Contact – –