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- W2886682023 abstract "Computer systems from HPC to data centers to PCs need to take running computations into account in order to maximize quality objectives while observing power constraints. We present PCOQ, a method that measures key parameters to control package (core + uncore) power, energy and performance, using DVFS plus choices of prefetch, instruction set type, and core count. We discuss algorithms and show results on a set of HPC codelets, comparing our results to race to halt and the OnDemand governors. We also discuss a variation of PCOQ, it is an off-line approximation method for running applications. We show that energy savings vs performance impact highly depend on data locality: 18% vs 50% CPU energy savings in LLC and RAM data sizes respectively." @default.
- W2886682023 created "2018-08-22" @default.
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- W2886682023 date "2018-08-13" @default.
- W2886682023 modified "2023-10-14" @default.
- W2886682023 title "Power-Constrained Optimal Quality for High Performance Servers" @default.
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- W2886682023 doi "https://doi.org/10.1145/3229710.3229749" @default.
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