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Economic Mechanisms for Managing Risk in Heterogeneous Datacenters

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Economic Mechanisms for Managing Risk in Heterogeneous Datacenters

  • 講者Benjamin C. Lee 教授 (Electrical and Computer Engineering, Duke University)
    邀請人:張原豪
  • 時間2014-01-02 (Thu.) 15:30 ~ 17:30
  • 地點資訊所新館106演講廳
摘要

As cloud computing proliferates, demand for datacenter computing capacity increases.  Moreover, we must increase capacity within today's megawatt-scale power budgets. Toward this goal, we present the case for building datacenters using processors and memories that were originally intended for mobile and embedded platforms. For web search, mobile processors are 5x more efficient than server processors. We quantify and mitigate the impact on query latency, relevance, and quality-of-service.  Mobile memories are 5.6x more efficient than server memories. We identify datacenter applications that can benefit from mobile memories. 

Mixing server and mobile hardware in a datacenter increases management complexity and we describe how datacenters might navigate this complexity with economic mechanisms. For settings where throughput is desired, we present a market in which users bid for heterogeneous hardware. For settings where fairness is desired, we present a game-theoretic mechanism that guarantees equitable hardware allocations.

BIO

Benjamin Lee is an assistant professor of Electrical and Computer Engineering at Duke University.  His research focuses on scalable technologies, power-efficient architectures, and high-performance applications.  He is also interested in the economics and public policy of computation. He has held visiting research positions at Microsoft Research, Intel Labs, and Lawrence Livermore National Lab. 

Dr. Lee received his B.S. at the University of California at Berkeley, S.M. and Ph.D. at Harvard University, and post-doctorate at Stanford University. He received the NSF CAREER Award in 2012. And his research has been honored as a Top Pick by IEEE Micro Magazine (2010), twice as a Research Highlight by Communications of the ACM (2010, 2011), and by an NSF Computing Innovation Fellowship (2009-10).