SCHEDULE: NOV 10-16, 2012
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Total Energy Optimization for High Performance Computing Data Centers
SESSION: Doctoral Showcase - Dissertation Research Showcase
EVENT TYPE: Doctoral Showcase
TIME: 11:15AM - 11:30AM
SESSION CHAIR: Yong Chen
Meeting energy and power requirements for huge exascale machines is a major challenge. Energy costs for data centers can be divided into two main categories: machine energy and cooling energy consumptions. This thesis investigates reduction in energy consumption for HPC data centers in both these categories. Our recent work on reducing cooling energy consumption shows that we can reduce cooling energy consumption by up to 63% using our temperature aware load balancer. In this work, we also demonstrate that data centers can reduce machine energy consumption by up to 28% by running different parts of the applications at different frequencies. The focus of our work is to gauge the potential for energy saving by reducing both machine and cooling energy consumption separately (and their associated execution time penalty) and then come up with a scheme that combines them optimally to reduce total energy consumption for large HPC data centers.
Yong Chen (Chair) - Texas Tech University
Osman Sarood - University of Illinois at Urbana-Champaign