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. 2022 May 11;16:837549. doi: 10.3389/fninf.2022.837549

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Copyright © 2022 Albers, Pronold, Kurth, Vennemo, Haghighi Mood, Patronis, Terhorst, Jordan, Kunkel, Tetzlaff, Diesmann and Senk.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Listing 1 — Excerpt of a config file in yaml-format for setting model, machine, and software parameters for benchmarking the multi-area model. When giving a list (e.g., for num_nodes), a job for each entry of the list is created. Model parameters: network_state describes particular model choices that induce different dynamical fixed points; model_time_sim defines the total model simulation time in ms; scaling_type sets up the simulation for either a weak- or a strong-scaling experiment. The former scales the number of neurons linearly with the used resources which might be ill-defined for anatomically constrained models. Machine parameters: num_nodes defines the number of nodes over which the scaling experiment shall be performed; tasks_per_node and threads_per_task specify the number of MPI tasks per node and threads per MPI task respectively. Software parameters: simulator and version describe which version of which simulator to use (and to install if not yet available on the machine).