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Low Power Solutions: A System Design Perspective

Low Power Solutions: A System Design Perspective. Nik Sumikawa. Low Power: Why?. 1. Standard Embedded Solutions. 2. 3. 3. Innovative Solutions. 4. 4. Solutions for Mobile Platforms. Contents. Low Power: Why?. Power vs. Performance Technology Scaling VLSI Embedded Technology Trend

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Low Power Solutions: A System Design Perspective

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  1. Low Power Solutions:A System Design Perspective NikSumikawa

  2. Low Power: Why? 1 Standard Embedded Solutions 2 3 3 Innovative Solutions 4 4 Solutions for Mobile Platforms Contents

  3. Low Power: Why? • Power vs. Performance • Technology Scaling • VLSI • Embedded • Technology Trend • Green Stimulus • Scaling Size Company Logo

  4. What You Should Think About • Low power design strategies • Components: Microcontrollers, peripherals, ect. • Low power design with hardware • Low power design with software • Low power design in mobile device Company Logo

  5. Low Power Embedded Systems • TELOS: • Low power wireless embedded system • Low duty cycle principle • Minimizes dynamic power consumption Company Logo

  6. Process Wake Up Sleep Mode Sleep Prep Deep Sleep Low Duty Cycle Principle Timer or Interrupt event

  7. Low Duty Cycle • Low processing to sleep ratio • Extended sleep period • Responsively: • fast wake-up and sleep times • Minimize Interrupts: • Context switching overhead Company Logo

  8. Low Duty Cycle: DMA • Direct Memory Access (DMA): • Controls bus and transfers data with minimal processor overhead • Significance • Transfer data while sleeping • Minimize processor overhead Company Logo

  9. Low Duty Cycle • Fails with significant processing • Alternatives: • Dynamic Voltage and Frequency Scaling (DVFS) • Dynamic Power Management (DPM) • Image: http://www.domainmagnate.com/wp-content/uploads/2009/03/failure-success.jpg

  10. Design Variables Energy Source Capacitance Dynamic Power Frequency Battery Voltage P = CVdd2f Dynamic Power

  11. Reducing Dynamic Power • Dynamic Voltage and Frequency Scaling • Scale voltage when sleeping/Idle • Voltage term quad. proportional to power • Reduce frequency • Minimize line capacitance • Long traces have large capacitance Company Logo

  12. Dynamic Power Management • Generalize power management • Multiple policies • Single-policy • Multiple-policy • Task-scaling Rajami and Brock [2]

  13. Single-policy Strategy • Idle Scaling (IS) • Operate at full speed when processing workload • Reduce the frequency and voltage when idle • Goal: • Reduce the CPU and bus frequencies • Meet continuous DMA requirements • Provide acceptable latency when resuming from idle Rajami and Brock [2]

  14. Multi-policy Strategies • Load scaling (LS): • Balance system operating point with current or predicted processing demands • Run system with minimal idle time • Other: • Manage systems state based on status of the systems energy source Rajami and Brock [2]

  15. Task-scaling Strategies • Application scaling (AS): • Used for workloads that are difficult to power manage • Audio and video processing • Begin processing next sample immediately • Operate a lower operating point • Increases to higher operating point when it begins to fall behind. Rajami and Brock [2]

  16. Results of DPM • IS: Idle Scaling LS: Load Scaling AS: Application Scaling • Frame-Scaling (FS): perfect knowledge of processing requirements of video frame Rajami and Brock [2]

  17. Too Many Low Power States • Disadvantages: • Confusion • Wrong low power state • Solution: • Minimize the number of state • Decrease complexity Image: http://kunaljanu.files.wordpress.com/2009/02/ ist2_1457667confusion-1.jpg

  18. Sources of Power Consumption • Microcontroller • Bus architecture • On chip communication • External communication • Memory hierarchy • Peripherals Rajami and Brock [2]

  19. Communication Architectures • Advanced Microcontroller Bus Architecture • ARM bus protocol for system-on-a-chip (SOC) • Advanced High Performance Bus (AHB) • Pipelined • Memory mapped • Up to 16 masters, 16 slaves • Advanced Peripheral Bus (APB) • Non pipelined • Single master, up to 16 peripherals Rajami and Brock [2]

  20. AMBA On-chip Bus Rajami and Brock [2]

  21. Power Profiling • 86% power consumed by logic • 14% power consumed by bus lines Rajami and Brock [2]

  22. Power Reduction Techniques • Power Management • Shut down bus interfaces to idle slaves • Bus Encoding • Reduces # of line transitions, but not bus transactions • Traffic Sequencing • Reduce multiple masters interleaving bus access Rajami and Brock [2]

  23. Power Reduction Techniques • No technique achieves large saving alone Rajami and Brock [2]

  24. Power vs Energy • Power is amount of energy over an amount of time (Watts = Joules / second) • Battery provides finite amount of energy • Goal: minimize energy use, not just power • In mobile systems we care about energy • Budget energy to prolong battery life Rajami and Brock [2]

  25. Static System Optimization • Compiler techniques • Instruction energy consumption profiling • Done empirically • Instruction reordering • Without affecting correctness • Improve register utilization • Reduce memory accesses • Reduce pipeline stalls

  26. Static System Optimization • Code Compression • Post compilation static optimization • Reduces storage size of instructions • Can have a large impact • Requires complex design space exploration • Goal for mobile system: reduce power consumption while preserving performance

  27. Code Compression Challenges • Random access decompression • Defining decodable block beginnings • Jump to new locations in program without decoding all blocks between • Solutions • Begin compressed blocks on byte boundaries • Store translation table • More efficient the compression, larger the table • Recalculate branch offsets to compressed addresses

  28. Code Compression Requirements • Additional hardware • Additional memory to store table • Decompression unit • Design decisions • Table generation/lookup • Compression technique

  29. Code Compression Implementation • SPARC ISA • Optimize consumption of complete SOC • Multiple iterations on binary • Instructions split into 4 categories • Group 1: immediate instructions (code = 0) • Group 2: branch instructions (code = 11) • Group 3: dictionary instructions (code = 100) • Group 4: uncompressed instr (code = 101)

  30. Update branch offsets Phase 4 Branch compression Phase 3 Immediate compression Phase 2 Markov model Phase 1 Diagram Optimized Binary Compiled Binary Company Logo

  31. As a Result… • Bus Compaction • Instructions transmitted no longer require entire bus • Use the extra lines to transmit the next compressed instruction

  32. Decompression Architecture • Pre-Cache • Decompression engine between memory/cache • Post-Cache • Decompression engine between cache/cpu

  33. Simulation • Full SOC simulation • 7 sample apps run

  34. Results

  35. INCLUDE?

  36. Results • Net energy saving observed • 22-82% power savings from code compression • What about additional hardware? • Bonus • Increased performance • Reduced area

  37. Verdict • Static power optimization • Potentially large payoff for little preprocessing • Still more sources of consumption • We’ve observed SOC savings • What about peripherals?

  38. Energy Budget Voice Call SMS Energy Budget Emails Pictures localization

  39. Energy Budget: Localization • How much of the energy budget should be given to localization? • Depends on the user • Grant increase allotment when localization is a higher priority

  40. 1 2 3 • GSM • Lower accuracy • Lower power requirement • GPS • Very accurate • Power Hungry • WiFi • Mod. Accurate • Mod. Power requirement Localizations Methods

  41. Power vs. Precision Localization Power: amount of energy required by peripheral in order to determine location Precision: Accuracy of the device used for localization Constandache, Gaonkar, Sayler, Choudhury, Cox [3]

  42. Power Consumption • 30 Second sampling intervals • Power Consumption: • GPS: High baseline • WiFi: Low baseline with high spikes • GSM: Low baseline with varying spikes Constandache, Gaonkar, Sayler, Choudhury, Cox [3]

  43. Power Consumption • 30 Second sampling intervals • Results: • GPS: increased baseline Company Logo

  44. Localization Accuracy • Accuracy varied based on location • ALE: Average Location Error • Wifi and GSM oversampled Company Logo

  45. Add Your Text Add Your Text Add Your Text Add Your Text Diagram Add Your Text Add Your Text Add Your Text Add Your Text Company Logo

  46. Diagram Add Your Text Add Your Text Add Your Text Company Logo

  47. Add Your Title ThemeGallery is a Design Digital Content & Contents mall developed by Guild Design Inc. Diagram Add Your Title ThemeGallery is a Design Digital Content & Contents mall developed by Guild Design Inc. Add Your Title ThemeGallery is a Design Digital Content & Contents mall developed by Guild Design Inc. Company Logo

  48. Text Diagram Text Text Add Your Title Text Company Logo

  49. Add Your Text B A C Microcontroller Add Your Text Sources D E Add Your Text Add Your Text Cycle Diagram Company Logo

  50. 2004 2001 2002 2003 Diagram Your Text Your Text Your Text Your Text Your Text Your Text Your Text Your Text Company Logo

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