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Project Proposal Presented by Michael Kazecki

Project Proposal Presented by Michael Kazecki. Outline. Background Algorithms Goals Ideas Proposal Introduction Motivation Implementation. Background. Hill-Climbing. Mid-point No. of Processors (P). Reduce DVFS. No. Continue until miss. Target miss. Yes.

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Project Proposal Presented by Michael Kazecki

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  1. Project Proposal Presented by Michael Kazecki

  2. Outline • Background • Algorithms • Goals • Ideas • Proposal • Introduction • Motivation • Implementation

  3. Background

  4. Hill-Climbing Mid-point No. of Processors (P) Reduce DVFS No Continue until miss Target miss Yes Choose optimum DVFS for that P just above miss Continue for another P` Disregard and switch sides Cost: L lg N No Better than previous Yes Optimum DVFS operating point

  5. Hill-Climbing Optimization Mid-point No. of Processors (P) Apply DVFS formula for that P Continue for another P` Disregard and switch sides No Better than previous Yes Optimum DVFS operating point

  6. Final Algorithm Hill-climbing + DVFS optimization Cost: alpha lg N alpha grows slower than L

  7. Goal • Dynamically optimizing power consumption of a parallel application • Low-overhead algorithms for dynamic optimization that produces optimal power savings.

  8. Ideas • Improve on existing algorithm developed to overcome local optima situations, such as the use of “jitter” or momentum. • Expand research in another dimension by varying each individual processor core DVFS • Propose a prediction based algorithm using past results to calculate DVFS in real-time

  9. Proposal Introduction • Develop a history based algorithm that is optimized for highly variable applications • Build a history table to track patterns in application’s behavior • Use a lookup registry to match current pattern to a suitable DVFS level

  10. Proposal Motivation • Target run-time power-performance adaptation of future processors that run non-repetitive parallel applications. • Maximizing power savings while delivering a specified level of performance in real-time with low overhead.

  11. Proposal Implementation • Hardware support • Requires cache and a register to support the history table and recent lookup • Requires real-time hardware power/performance monitoring • Software support • After search phase, mechanism needed to control DVFS and number of processors

  12. End Questions?

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