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Access Type

Open Access Thesis

Document Type


Degree Program

Electrical & Computer Engineering

Degree Type

Master of Science in Electrical and Computer Engineering (M.S.E.C.E.)

Year Degree Awarded


Month Degree Awarded



Computing researchers have long focused on improving energy-efficiency?the amount of computation per joule? under the implicit assumption that all energy is created equal. Energy however is not created equal: its cost and carbon footprint fluctuates over time due to a variety of factors. These fluctuations are expected to in- tensify as renewable penetration increases. Thus in my work I introduce energy-agility a design concept for a platform?s ability to rapidly and efficiently adapt to such power fluctuations. I then introduce a representative application to assess energy-agility for the type of long-running, parallel, data-intensive tasks that are both common in data centers and most amenable to delays from variations in available power. Multiple variants of the application are implemented to illustrate the fundamental tradeoffs in designing energy-agile parallel applications. I find that with inactive power state transition latencies of up to 15 seconds, a design that regularly ”blinks” servers out- performs one that minimizes transitions by only changing power states when power varies. While the latter approach has much lower transition overhead, it requires additional I/O, since servers are not always concurrently active. Unfortunately, I find that most server-class platforms today are not energy-agile: they have transition la- tencies beyond one minute, forcing them to minimize transition and incur additional I/O.


First Advisor

David Emory Irwin

Second Advisor

Michael Zink

Third Advisor

Tilman Wolf