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Represented by: Majid Malaika

An Analysis of Efficient Multi-Core Global Power Management Policies: Maximizing Performance for a Given Power Budget. Represented by: Majid Malaika. Authors: Canturk Isci†, Alper Buyuktosunoglu†, Chen-Yong Cher†, Pradip Bose† and Margaret Martonosi. Agenda. Background Motivation

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Represented by: Majid Malaika

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  1. An Analysis of Efficient Multi-Core Global Power Management Policies: Maximizing Performance for a Given Power Budget Represented by: Majid Malaika Authors: Canturk Isci†, Alper Buyuktosunoglu†, Chen-Yong Cher†, Pradip Bose† and Margaret Martonosi

  2. Agenda • Background • Motivation • Contribution • Overview of the global power management policy • Core Power Modes • Global Power Management Policies • Independent Per-Core Power Management • Simulation • Evaluation • Q&A

  3. Background • Power Management are desired for many reasons: • For portable devices • For Desktop systems • For Supercomputers P = V^2 * F • Power is proportional to voltage squared • Current is also proportional to voltage

  4. Cont. Background • Multicore architecture has become more important than ever due to the Famous “Walls” • With more cores on the dice, Power and temperature problems are becoming more and more crucial

  5. Motivation • How to enforce a power budget through global power manager? • How to minimize power given a performance target?

  6. Contributions • Introduced the concept of Global Power Manager (PM) • Developed a fast static power management analysis tool • Evaluated different PM policies (with different focus such as prioritization, fairness, throughput)

  7. Global CMP Power Management Overview • To exploit the widely known variability in demand and characteristics of the input workloads • Adaptive response to “Phases” for power-efficient computing.

  8. Cont. Global CMP Power Management Overview

  9. Cont. Global CMP Power Management Overview the loop of PM’s work • PM periodically collects power-performance data from local monitors • PM reports it to OS • OS returns power budget, thread affinities, high-level scheduling and load-balancing plan to PM • PM decides the power-mode of each core based on those info

  10. Cont. Global CMP Power Management Overview Preconditions Each core • has its own dynamic controller • has its power-performance monitor (e.g. current monitor, perf monitoring counter hw) • can be running in multiple power modes

  11. Core Power Modes • Three Power Modes: • Turbo • Efficient1(Eff1) • Efficient2(Eff2) • The target is to achieve PowerSavings : PerformanceDegradation ratio of 3 : 1

  12. Cont. Core Power Modes • Target

  13. Cont. Core Power Modes • Transition overhead between Power Modes • The duration of each monitored interval is called “Explore time” and is set to 500 MS. • Low overhead (1 to 4%)

  14. Global Power Management Policies • Introduced three policies for different objectives: • Priority • PullhiPushLo • MaxBIPS

  15. Cont. Global Power Management Policies • Priority • Assigns Different Priority to different tasks • Highest Priority to highest Core (Example Core4) • Lowest Priority to Lowest Core (Example Core1) • In policy implementation it tries to run the highest AFAP • Prefer to slow down the first core in case of budget overshoot

  16. Cont. Global Power Management Policies • PullhiPushLo • Tries to balance the power consumption of each core • It slows down the highest core in case of a budget overshoot • And by speeding up the lowest power core when there is available

  17. Cont. Global Power Management Policies • MaxBIPS • Targets at optimizing the system throughput • Predicts and choose the Power Mode that Maximizes the throughput at each explore time • MaxBIPS does that by predicting the corresponding power and BIPS values for each power mode • It then chooses the combination with the highest throughput that satisfies the current power budget

  18. Independent Per-Core Power Management • Chip-Wide DVFS • Simpler alternative • No Synchronization across cores • Simplified OS and Hardware • All cores transition together into Turbo, Eff1, Eff2 at each explore time based on budget constraints

  19. Simulation • Based on IBM Turandot simulator • Power statistics from IBM PowerTimer • The list of core parameter

  20. Cont. Simulation • Target 3:1 • Estimation

  21. Evaluation

  22. Cont. Evaluation

  23. Cont. Evaluation

  24. References • C. Isci et al., "An Analysis of Efficient Multi-Core Global Power Management Policies: Maximizing Performance for a Given Power Budget"

  25. Q&A The End

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