Sangam: A Confluence of Knowledge Streams

Managing Memory for Power, Performance, and Thermal Efficiency

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dc.contributor Computer Science
dc.contributor Cameron, Kirk W.
dc.contributor Beihl, Gary M.
dc.contributor Butt, Ali R.
dc.contributor Nikolopoulos, Dimitrios S.
dc.contributor Ribbens, Calvin J.
dc.creator Tolentino, Matthew Edward
dc.date 2014-03-14T20:07:46Z
dc.date 2014-03-14T20:07:46Z
dc.date 2009-02-18
dc.date 2009-02-24
dc.date 2009-04-08
dc.date 2009-04-08
dc.date.accessioned 2023-03-01T08:10:16Z
dc.date.available 2023-03-01T08:10:16Z
dc.identifier etd-02242009-162329
dc.identifier http://hdl.handle.net/10919/26301
dc.identifier http://scholar.lib.vt.edu/theses/available/etd-02242009-162329/
dc.identifier.uri http://localhost:8080/xmlui/handle/CUHPOERS/276592
dc.description Extraordinary improvements in computing performance, density, and capacity have driven rapid increases in system energy consumption, motivating the need for energy-efficient performance. Harnessing the collective computational capacity of thousands of these systems can consume megawatts of electrical power, even though many systems may be underutilized for extended periods of time. At scale, powering and cooling unused or lightly loaded systems can waste millions of dollars annually. To combat this inefficiency, we propose system software, control systems, and architectural techniques to improve the energy efficiency of high-capacity memory systems while preserving performance. We introduce and discuss several new application-transparent, memory management algorithms as well as a formal analytical model of a power-state control system rooted in classical control theory we developed to proportionally scale memory capacity with application demand. We present a prototype implementation of this control-theoretic runtime system that we evaluate on sequential memory systems. We also present and discuss why the traditional performance-motivated approach of maximizing interleaving within memory systems is problematic and should be revisited in terms of power and thermal efficiency. We then present power-aware control techniques for improving the energy efficiency of symmetrically interleaved memory systems. Given the limitations of traditional interleaved memory configurations, we propose and evaluate unorthodox, asymmetrically interleaved memory configurations. We show that when coupled with our control techniques, significant energy savings can be achieved without sacrificing application performance or memory bandwidth.
dc.description Ph. D.
dc.format application/pdf
dc.publisher Virginia Tech
dc.relation dissertation_final-post-grad-review.pdf
dc.rights In Copyright
dc.rights http://rightsstatements.org/vocab/InC/1.0/
dc.subject Energy Efficiency
dc.subject Control Theory
dc.subject Memory Management
dc.subject Operating Systems
dc.title Managing Memory for Power, Performance, and Thermal Efficiency
dc.type Dissertation


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