%0 Conference Paper
%A Akar, Nora Abi
%A Cumming, Ben
%A Karakasis, Vasileios
%A Kusters, Anne
%A Klijn, Wouter
%A Peyser, Alexander
%A Yates, Stuart
%T Arbor — A Morphologically-Detailed Neural Network Simulation Library for Contemporary High-Performance Computing Architectures
%I IEEE
%M FZJ-2019-02058
%@ 978-1-7281-1644-0
%P 274-282
%D 2019
%X 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
%B 2019 27th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP)
%C 13 Feb 2019 - 15 Feb 2019, Pavia (Italy)
Y2 13 Feb 2019 - 15 Feb 2019
M2 Pavia, Italy
%F PUB:(DE-HGF)8 ; PUB:(DE-HGF)7
%9 Contribution to a conference proceedingsContribution to a book
%U <Go to ISI:>//WOS:000467257000039
%R 10.1109/EMPDP.2019.8671560
%U https://juser.fz-juelich.de/record/861612