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Published byNigel Evans Modified over 9 years ago
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Project Proposal Presented by Michael Kazecki
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Outline Background –Algorithms Goals Ideas Proposal –Introduction –Motivation –Implementation
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Background
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Hill-Climbing Mid-point No. of Processors (P) Target miss Reduce DVFS Choose optimum DVFS for that P just above miss Yes Continue until miss Continue for another P` Better than previous Yes No Disregard and switch sides Cost: L lg N No Optimum DVFS operating point
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Hill-Climbing Optimization Mid-point No. of Processors (P) Apply DVFS formula for that P Continue for another P` Optimum DVFS operating point Better than previous Yes Disregard and switch sides No
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Final Algorithm Hill-climbing + DVFS optimization Cost: alpha lg N alpha grows slower than L
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Goal Dynamically optimizing power consumption of a parallel application Low-overhead algorithms for dynamic optimization that produces optimal power savings.
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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
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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
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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.
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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
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End Questions?
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