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Data-intensive workloads demand a large portion of data center resources and consume massive amounts of energy. Energy conservation for data-intensive computing requires enabling technology to provide detailed and systemic energy information and to identify the energy inefficiencies in the underlying system hardware and software. In this work, we address this need and present eTune, a fine-grained,...
Future large scale high performance supercomputer systems require high energy efficiency to achieve exaflops computational power and beyond. Despite the need to understand energy efficiency in high-performance systems, there are few techniques to evaluate energy efficiency at scale. In this paper, we propose a system-level iso-energy-efficiency model to analyze, evaluate and predict energy-performance...
In energy efficient high end computing, a typical problem is to find an energy-performance efficient resource allocation for computing a given workload. An analytical solution to this problem includes two steps: first estimating the performances and energy costs for the workload running with various resource allocations, and second searching the allocation space to identify the optimal allocation...
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