[Back] [PDF]  Energy-Efficient Resource Management for High-Performance Computing Platforms Ziliang Zong Department of Computer Science and Software Engineering Auburn University Auburn, Alabama 36830, USA In the past decade, high-performance computing (HPC) platforms like clusters and computational grids have been widely used to solve challenging and rigorous engineering tasks in industry and scientific applications. Due to extremely high energy cost, reducing energy consumption has become a major concern in designing economical and environmentally friendly HPC infrastructures for many applications.  In this dissertation, we first describe a general architecture for building energy-efficient HPC infrastructures, where energy-efficient techniques can be incorporated in each layer of the proposed architecture. Next, we developed an array of energy-efficient scheduling algorithms as well as energy-aware load balancing for high-performance clusters, computational grids, and large-scale storage systems. The primary goal of this dissertation research is to minimize energy consumption while maintaining reasonably high performance by incorporating energy-aware resource management techniques to HPC platforms. We have conducted extensive simulation experiments using both synthetic and real world applications to quantitatively evaluate both energy efficiency and performance of our proposed energy-efficient scheduling and load balancing strategies. Experimental results show that our approaches can reduce energy dissipation in HPC platforms without significantly degrading system performance. A Dissertation Submitted to  the Graduate Faculty of Auburn University in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Auburn, Alabama August 9, 2008 Acknowledgments The work reported in this dissertation was supported by the US National Science Foundation under Grants No. CCF-0742187 and No. CNS-0757778, and Auburn University under a startup grant.