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In the past decade, high-performance cluster computing platforms 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 cluster computing
infrastructures for many high-performance applications. The primary focus of this talk is to illustrate how to improve energy efficiency of clusters and storage systems without significantly degrading performance. In this talk, we will first describe a general architecture
for building energy-efficient cluster computing platforms. Then, we will outline several energyefficient scheduling algorithms designed for high-performance clusters and large-scale storage systems. The experimental results using both synthetic and real world applications
show that energy dissipation in clusters can be reduced with a marginal degradation of system performance.
In the past decade, high-performance cluster computing platforms 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 cluster computing infrastructures for many high-performance applications. The primary focus of this talk is to illustrate how to improve energy efficiency of clusters and storage systems without significantly degrading performance. In this talk, we will first describe a general architecture for building energy-efficient cluster computing platforms. Then, we will outline several energyefficient scheduling algorithms designed for high-performance clusters and large-scale storage systems. The experimental results using both synthetic and real world applications show that energy dissipation in clusters can be reduced with a marginal degradation of system performance.
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