Xiao Qin  [Back to Home]

BUD: A Buffer-Disk Architecture for Energy Conservation in Parallel Disk Systems 

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Department of Computer Science Faculty

Xiao Qin (PI), Assistant Professor, Auburn University

Tao Xie (Co-PI), Assistant Professor, San Diego State University

Mais Nijim, Assistant Professor, University of Southern Mississippi

LANL Scientist and Intel Technical Staff

Peter C. Lichtner (Co-PI), Hydrology, Geochemistry, and Geology Group, Los Alamos National Laboratory

Yiming Yang, Senior Software Engineer, Intel Corporation

Students 

Ziliang Zong [Ph.D. Candidate | Awards Total: 12 | Publications Total: 23; Journal Papers: 7; Conference Papers: 16]

Dissertation Research: Conserving Energy in Clusters through Resource Allocation.

Minimizing power dissipation is an important requirement in developing resource management systems for clusters. In this work, we investigate resource allocation solutions that conserve energy in clusters while retaining high performance. Our resource allocation approaches will judiciously allocate resources of a cluster computing system to satisfy performance needs of parallel applications and achieve significant energy savings. Read more...

Kiranmai Bellam [Ph.D. Student | Awards Total: 3 | Publications Total: 15; Journal Papers: 5; Conference Papers: 10]

Dissertation Research: Fault Tolerance, Security, and Energy Issues in Real-Time Systems.

Fault tolerance, security, and energy issues in modern real-time systems are of critical importance. This work is intended to seamlessly integrate security services and energy conservation techniques for real-time systems while endeavoring to achieving high system reliability. Read more...

Xiaojun Ruan [Ph.D. Student | Publications Total: 11; Journal Papers: 4; Conference Papers: 7]

Thesis Research: Dynamic Voltage Scaling for Parallel Applications on Clusters.

In this study we design and implement a scheduling algorithm that makes use of dynamic voltage scaling to effectively reduce energy consumption of parallel applications running on cluster computing systems.

Adam Manzanares [Ph.D. Student | Awards: 2 | Publications Conference Papers: 1] 

Dissertation Research: Energy Efficient Wireless Storage Systems.

This study addresses the issue of modeling energy-efficient wireless storage systems and wireless network interconnections. Adam's work on energy conservation for high-performance clusters appeared in the proceedings of the 8th IEEE International Conference on Cluster Computing (Cluster'06), Sept. 2006. Read more...

Gourav Tilve [M.S. Student | Publications]

Thesis Research: Energy-Aware Data Prefetching in Disk-Based Buffers.

In this study we aim at developing novel data prefetching strategies to conserve energy in large scale storage systems with buffer disks while improving usage of disk-based buffers.

Nicholas W. O'Connor [M.S. Student | Awards Total: 1 | Publications Conference Papers: 2]

Research Project: Energy Consumption Models for Disk Systems.

This study addresses the issue of modeling energy consumption in server and embedded disk systems. Read more...

Matthew E. Briggs [Undergraduate Student | Awards Total: 1 | Publications Conference Papers: 2] 

Senior Research Project: Energy-Efficient Disk Buffer Disks.

The goal of this research is to develop a novel buffer-disk architecture that will provide significant energy savings while achieving low-cost and high-performance for parallel disks. In this project we will take an organized approach to implementing energy-saving techniques for parallel disks and simulating energy-efficient parallel disk systems. Read more...

Tenzin Doleck [Undergraduate Student]

Senior Research Project: Energy-Efficient Storage Systems.

Improving the energy efficiency of storage systems is an intrinsic requirement of next generation large-scale computing systems, because a storage subsystem can represent 27% of the energy consumed in a data center. The goal of this research is to investigate energy conservation techniques that will provide significant energy savings while achieving high-performance for storage systems.


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Updated on 8/2/2007