2015 · 12 citations · 6 references
ComputingComputer ScienceHigh-performance ComputingComputational NeuroscienceComputer ArchitectureParallel ComputingGraphics Processing Unit ArchitectureNeural ModelingNeural NetworksNeural System ModelingParallel ArchitecturesSpiking Neural NetworksApplication Performance AssessmentApplication Performance OptimizationApplication-level PerformanceBiophysically Detailed Neuron ModelsHigh-performance Computing For NeuroscienceMorphologically Detailed Neuron ModelsNeuron SimulationsSupercomputer Architecture
A part of large-scale future supercomputing architectures will rely on a combination of IBM POWER9 and Nvidia GPU processors. In order to anticipate software design, implementation and optimization decisions and optimally prepare scientific applications targetting exascale computing, it is mandatory to already analyze application performance on prototype hardware. In this article an evaluation of the performance of the IBM POWER8 system is provided in the context of NEURON software, a widely-used computational neuroscientific application modeling large-scale neuronal network using detailed morphologies. This evaluation describes in details how to accurately measure the performance of the system but also provides a first detailed performance analysis of representative kernels of NEURON. From this analysis, improvements can be suggested at the level of the application but also at the level of the performance measurement and system setup.
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Samuel Williams, Andrew Waterman, David A. Patterson · Communications of the ACM · 2009 · 2.4K citations · Full text
A complete anytime algorithm for number partitioning
Richard E. Korf · Artificial Intelligence · 1998 · 230 citations
IBM POWER7 multicore server processor
Balaram Sinharoy, R. Kalla, William J. Starke et al. · IBM Journal of Research and Development · 2011 · 159 citations