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Ph.D. Dissertation Defense: Inseok Choi
Tuesday, April 15, 2014
9:15 a.m.
2460 AVW
For More Information:
Maria Hoo
301 405 3681
mch@umd.edu

ANNOUNCEMENT: Ph.D. Dissertation Defense

Name: Inseok Choi

Committee:
Professor Donald Yeung, Chair/Advisor
Professor Manoj Franklin
Professor Gang Qu
Professor Rajeev Barua
Professor Alan Sussman, Dean's Representative

Date/Time: Tuesday, April 15, 2014, 9:15 AM

Location: AV Williams building, 2460 (AVW2460)

Title: GREEDY COORDINATE DESCENT CMP MULTI-LEVEL CACHE RESIZING

Abstract:

Hardware designers are constantly looking for ways to squeeze waste out of architectures to achieve better power efficiency. Cache resizing is a technique that can remove wasteful power consumption in caches. The idea is to determine the minimum cache a program needs to run at near-peak performance, and then reconfigure the cache to implement this efficient capacity. While there has been significant previous work on cache resizing, existing techniques have focused on controlling resizing for a single level of cache only. This sacrifices significant opportunities for power savings in modern CPU hierarchies which routinely employ 3 levels of cache. Moreover, as CMP scaling will likely continue for the foreseeable future, eliminating wasteful power consumption from a CMP multi-level cache hierarchy is crucial to achieve better power efficiency.

In this dissertation, we propose a noble technique, greedy coordinate descent CMP multi-level cache resizing, that minimizes a power consumption while maintaining a high performance. We simutaneously resizes all caches in a modern CMP cache hierarchy to minimize the power consumption. Specifically, our approach predicts the power consumption and the performance level without direct evaluations. We also develop greedy coordinate descent method to search an optimal cache configuration utilizing power efficiency gain (PEG) that we propose in this dissertation.

This dissertation makes three contributions for a CMP multi-level cache resizing. First, we discover the limits of power savings and performance. This limit study identifies the potential power savings in a CMP multi-level cache hierarchy when wasteful power consumption is eliminated. Second, we propose a prediction-based greedy coordinate descent (GCD) method to find an optimal cache configuration and to orchestrate them. Third, we implement online GCD techniques for a CMP multi-level cache resizing. Our approach exhibits 13.9% power savings and achieves 91% of the power savings of the static oracle cache hierarchy configuration.

 

 

This Event is For: Graduate • Faculty

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