Reference : Evaluating the HPC Performance and Energy-Efficiency of Intel and ARM-based systems w...
Reports : Internal report
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/17025
Evaluating the HPC Performance and Energy-Efficiency of Intel and ARM-based systems with synthetic and bioinformatics workloads
English
Plugaru, Valentin mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Varrette, Sébastien mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Pinel, Frédéric mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Bouvry, Pascal mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Feb-2014
CSC
[en] High Performance Computing ; Scientific Computing ; Bioinformatics ; Parallel processing ; Microarchitecture ; Benchmark testing ; Performance analysis
[en] The increasing demand for High Performance Computing (HPC) paired with the higher power requirements of the ever-faster systems has led to the search for both performant and more energy-efficient architectures. This article compares and contrasts the performance and energy efficiency of two modern, traditional Intel Xeon and low power ARM-based clusters, which are tested with the recently developed High Performance Conjugate Gradient (HPCG) benchmark and the ABySS, FASTA and MrBayes bioinformatics applications. We show a higher Performance per Watt valuation of the ARM cluster, and lower energy usage during the tests, which does not offset the much faster job completion rate obtained by the Intel cluster, making the latter more suitable for the considered workloads given the disparity in the performance results.
University of Luxembourg: High Performance Computing - ULHPC
Researchers ; Professionals ; Students ; General public
http://hdl.handle.net/10993/17025

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