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Energy Scale-Down in System Design: Optimizations for Reducing Power

This talk focuses on energy scale-down for mobile devices and explores optimizations to reduce power consumption in display, processor, and wireless components.

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Energy Scale-Down in System Design: Optimizations for Reducing Power

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  1. 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

  2. Broader context • Energy scale-down one component of broader power management work • This talk will focus on scale-down for mobile devices Power and energy management Enterprise systems Power costs & cooling Mobile systems Battery life display wireless CPU Partha Ranganathan E-scale project, HP Labs

  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 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

  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 Partha Ranganathan E-scale project, HP Labs

  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 Partha Ranganathan E-scale project, HP Labs

  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 • 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

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

  8. 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 Overall results Partha Ranganathan E-scale project, HP Labs

  9. e 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

  10. 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

  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 Partha Ranganathan E-scale project, HP Labs

  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., …) Partha Ranganathan E-scale project, HP Labs

  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 emails • But display power is constant all the time • Can we provide a means for energy to scale-down with lower usage? Partha Ranganathan E-scale project, HP Labs

  14. Laptops PDAs,Handhelds 3G Phones,Automotive DigitalCamera&Camcorders 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 Partha Ranganathan E-scale project, HP Labs

  15. Software support: energy-aware user interfaces (DarkWindows) Approximate user interest to window of focus Automatic power-aware adaptation of background brightness/color Energy-aware user interfaces Partha Ranganathan E-scale project, HP Labs

  16. Xvnc X protocol VNC protocol Applications VNC Server VNC Viewer TrackFocus Window Change pixel values in framebuffer Xvnc VNC Viewer Original Framebuffer Modified Framebuffer 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 Partha Ranganathan E-scale project, HP Labs

  17. Benefits from energy adaptivity Partha Ranganathan E-scale project, HP Labs

  18. Power benefits from different interfaces Benefits from both hardware and software Broad acceptance of user interfaces in user study Power savings Partha Ranganathan E-scale project, HP Labs

  19. Energy savings function of user preference Power savings: sensitivity experiments Partha Ranganathan E-scale project, HP Labs

  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 Partha Ranganathan E-scale project, HP Labs

  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 Partha Ranganathan E-scale project, HP Labs

  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 Partha Ranganathan E-scale project, HP Labs

  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 Partha Ranganathan E-scale project, HP Labs

  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) Partha Ranganathan E-scale project, HP Labs

  25. 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 Power benefits Partha Ranganathan E-scale project, HP Labs

  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 Partha Ranganathan E-scale project, HP Labs

  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 Partha Ranganathan E-scale project, HP Labs

  28. Listen Interval 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 Partha Ranganathan E-scale project, HP Labs

  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 Partha Ranganathan E-scale project, HP Labs

  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 Partha Ranganathan E-scale project, HP Labs

  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 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: partha.ranganathan@hp.com Partha Ranganathan E-scale project, HP Labs

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