TY  - JOUR
AU  - Feldotto, Benedikt
AU  - Eppler, Jochen Martin
AU  - Jimenez-Romero, Cristian
AU  - Bignamini, Christopher
AU  - Gutierrez, Carlos Enrique
AU  - Albanese, Ugo
AU  - Retamino, Eloy
AU  - Vorobev, Viktor
AU  - Zolfaghari, Vahid
AU  - Upton, Alex
AU  - Sun, Zhe
AU  - Yamaura, Hiroshi
AU  - Heidarinejad, Morteza
AU  - Klijn, Wouter
AU  - Morrison, Abigail
AU  - Cruz, Felipe
AU  - McMurtrie, Colin
AU  - Knoll, Alois C.
AU  - Igarashi, Jun
AU  - Yamazaki, Tadashi
AU  - Doya, Kenji
AU  - Morin, Fabrice O.
TI  - Deploying and Optimizing Embodied Simulations of Large-Scale Spiking Neural Networks on HPC Infrastructure
JO  - Frontiers in neuroinformatics
VL  - 16
SN  - 1662-5196
CY  - Lausanne
PB  - Frontiers Research Foundation
M1  - FZJ-2022-02232
SP  - 884180
PY  - 2022
AB  - Simulating the brain-body-environment trinity in closed loop is an attractive proposal to investigate how perception, motor activity and interactions with the environment shape brain activity, and vice versa. The relevance of this embodied approach, however, hinges entirely on the modeled complexity of the various simulated phenomena. In this article, we introduce a software framework that is capable of simulating large-scale, biologically realistic networks of spiking neurons embodied in a biomechanically accurate musculoskeletal system that interacts with a physically realistic virtual environment. We deploy this framework on the high performance computing resources of the EBRAINS research infrastructure and we investigate the scaling performance by distributing computation across an increasing number of interconnected compute nodes. Our architecture is based on requested compute nodes as well as persistent virtual machines; this provides a high-performance simulation environment that is accessible to multi-domain users without expert knowledge, with a view to enable users to instantiate and control simulations at custom scale via a web-based graphical user interface. Our simulation environment, entirely open source, is based on the Neurorobotics Platform developed in the context of the Human Brain Project, and the NEST simulator. We characterize the capabilities of our parallelized architecture for large-scale embodied brain simulations through two benchmark experiments, by investigating the effects of scaling compute resources on performance defined in terms of experiment runtime, brain instantiation and simulation time. The first benchmark is based on a large-scale balanced network, while the second one is a multi-region embodied brain simulation consisting of more than a million neurons and a billion synapses. Both benchmarks clearly show how scaling compute resources improves the aforementioned performance metrics in a near-linear fashion. The second benchmark in particular is indicative of both the potential and limitations of a highly distributed simulation in terms of a trade-off between computation speed and resource cost. Our simulation architecture is being prepared to be accessible for everyone as an EBRAINS service, thereby offering a community-wide tool with a unique workflow that should provide momentum to the investigation of closed-loop embodiment within the computational neuroscience community.
LB  - PUB:(DE-HGF)16
C6  - 35662903
UR  - <Go to ISI:>//WOS:000805555900001
DO  - DOI:10.3389/fninf.2022.884180
UR  - https://juser.fz-juelich.de/record/907815
ER  -