Hauptseite > Publikationsdatenbank > Arbor — A Morphologically-Detailed Neural Network Simulation Library for Contemporary High-Performance Computing Architectures > print

001     861612
005     20210130000904.0
020 _ _ |a 978-1-7281-1644-0
024 7 _ |a 10.1109/EMPDP.2019.8671560
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037 _ _ |a FZJ-2019-02058
100 1 _ |a Akar, Nora Abi
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111 2 _ |a 2019 27th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP)
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|d 2019-02-13 - 2019-02-15
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245 _ _ |a Arbor — A Morphologically-Detailed Neural Network Simulation Library for Contemporary High-Performance Computing Architectures
260 _ _ |c 2019
|b IEEE
300 _ _ |a 274-282
336 7 _ |a CONFERENCE_PAPER
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336 7 _ |a Contribution to a book
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520 _ _ |a We 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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536 _ _ |a HBP SGA1 - Human Brain Project Specific Grant Agreement 1 (720270)
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700 1 _ |a Cumming, Ben
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700 1 _ |a Karakasis, Vasileios
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700 1 _ |a Kusters, Anne
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700 1 _ |a Klijn, Wouter
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700 1 _ |a Peyser, Alexander
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700 1 _ |a Yates, Stuart
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773 _ _ |a 10.1109/EMPDP.2019.8671560
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