This project develops a testbed for experimentation with energy saving in data centers via holistic management of both the computing and cooling subsystems. It instruments a large computing cluster at the University of Illinois that reproduces representative dynamics of energy consumption in data centers. Understanding heat and energy dynamics in large computing systems requires detailed sensing and control on both the computing and cooling side. The goal is to produce models and algorithms that significantly contribute to energy optimization research leading to reductions in carbon footprint and operating costs of contemporary computing clusters. The testbed developed in this project focuses primarily on understanding and improving software-controlled mechanisms for energy optimization in systems that exhibit non-trivial coupled thermal and computational dynamics, called thermo-computational systems, towards better energy management of data centers. When complete, it is likely to become the first and largest open testbed geared for enabling high quality research on large thermo-computational systems. The project is motivated by the increasing energy cost of data centers, which is estimated at more than $4.5 billion annually and is expected to grow at a rate of 12% in the absence of intervention. According to the EPA, most of this cost is avoidable. If successful, the project will therefore contribute significantly to both the economy and the environment by resulting in savings in both energy cost and carbon footprint.
