Enabling Large-Scale Simulations With the GENESIS Neuronal Simulator - Crone, Joshua C.; Vindiola, Manuel M.; Yu, Alfred B.; Boothe, David L.; Beeman, David; Oie, Kelvin S.; Franaszczuk, Piotr J. (Frontiers in Neuroinformatics, 2019)
In this paper, we evaluate the computational performance of the GEneral NEural SImulation System (GENESIS) for large scale simulations of neural networks. While many benchmark studies have been performed for large scale simulations with leaky integrate-and-fire neurons or neuronal models with only a few compartments, this work focuses on higher fidelity neuronal models represented by 50-74 compartments per neuron. After making some modifications to the source code for GENESIS and its parallel implementation, PGENESIS, particularly to improve memory usage, we find that PGENESIS is able to efficiently scale on supercomputing resources to network sizes as large as 9 x 106 neurons with 18 x 109 synapses and 2.2 x 106 neurons with 45 x 109 synapses. The modifications to GENESIS that enabled these large scale simulations have been incorporated into the May 2019 Official Release of PGENESIS 2.4 available for download from the GENESIS web site (genesis-sim.org).