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The latest top 10 supercomputers are dominated by heterogeneous systems with CPUs and accelerators (GPU or Xeon Phi) tightly coupled together. As the heterogeneity of future high performance computing systems keeps increasing, it becomes paramount to judiciously use CPUs and accelerators to improve performance and/or reduce energy consumption. The widely used programming model today is to offload...
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,...
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