New Publication: Arbor — A Morphologically-Detailed Neural Network Simulation Library for Contemporary High-Performance Computing Architectures,

13th February 2019 07:00 AM
13th February 2019 08:00 AM

Akar, N. A. ; Cumming, B. (Corresponding author); Karakasis, V. ; Kusters, A.; Klijn, W.; Peyser, A. (Corresponding author); Yates, S..

2019 27th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), Pavia, Italy, 2019, pp. 274-282. doi: 10.1109/EMPDP.2019.867156

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.


Last Modified: 16.08.2022