Pow!:
Maximizing Performance in Power-Constrained Environments
The EPA estimates that in 2006, the nation’s servers and data centers collectively consumed approximately 61 billion kilowatt-hours, or 1.5% of total US electricity consumption, at a total cost of approximately $4.5 billion. This level is expected to double again by 2011 as more and more applications shift from the desktop to a server-based computing paradigm.
The power problem is particularly pronounced in large CPU-intensive server farms, composed of tens of thousands of servers. Constraints on the amount of available power often limit the number of servers that companies can run to a number that is below demand. As a result, the ‘power ceiling’ on server farms will increasingly impact companies’ ability to scale their businesses, satisfy their customers, and optimize their operational efficiencies.
Pow! develops optimal power and workload allocation policies to get more performance from the available power. This is done by merging advanced queueing, optimization, and stochastic process theories to produce new, non-conventional analytical models. In preliminary tests, POW has achieved improved response times ranging from 2x to 5x over current methods.
See Pow Poster (790 KB)
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Pow! Team:
- Mor-Harchol-Balter, Associate Professor, Computer Science Department – Education, Carnegie Mellon
- Anshul Gandhi, Ph.D. student, Computer Science Department, Carnegie Mellon
- Varun Gupta, Ph.D. student, Computer Science Department, Carnegie Mellon
Donald Jones Center/ Olympus Interns:
- Matthew Mariett, Tepper School of Business, MBA
- Mark Prince,Tepper School of Business, MBA
- Masahiro Ogiso, Tepper School of Business, MBA
  CS/IT |
  GreenTech/Energy |
