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000861612 037__ $$aFZJ-2019-02058
000861612 1001_ $$0P:(DE-HGF)0$$aAkar, Nora Abi$$b0
000861612 1112_ $$a2019 27th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP)$$cPavia$$d2019-02-13 - 2019-02-15$$wItaly
000861612 245__ $$aArbor — A Morphologically-Detailed Neural Network Simulation Library for Contemporary High-Performance Computing Architectures
000861612 260__ $$bIEEE$$c2019
000861612 300__ $$a274-282
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000861612 520__ $$aWe introduce Arbor, a performance portable library for simulation of large networks of multi-compartment neurons on HPC systems. Arbor is open source software, developed under the auspices of the HBP. The performance portability is by virtue of back-end specific optimizations for x86 multicore, Intel KNL, and NVIDIA GPUs. When coupled with low memory overheads, these optimizations make Arbor an order of magnitude faster than the most widely-used comparable simulation software. The single-node performance can be scaled out to run very large models at extreme scale with efficient weak scaling.Keywords: HPC;GPU;neuroscience;neuron;software
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000861612 7001_ $$0P:(DE-HGF)0$$aCumming, Ben$$b1$$eCorresponding author
000861612 7001_ $$0P:(DE-HGF)0$$aKarakasis, Vasileios$$b2
000861612 7001_ $$0P:(DE-Juel1)166193$$aKusters, Anne$$b3$$ufzj
000861612 7001_ $$0P:(DE-Juel1)168169$$aKlijn, Wouter$$b4$$ufzj
000861612 7001_ $$0P:(DE-Juel1)161525$$aPeyser, Alexander$$b5$$eCorresponding author$$ufzj
000861612 7001_ $$0P:(DE-HGF)0$$aYates, Stuart$$b6
000861612 773__ $$a10.1109/EMPDP.2019.8671560
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