Scalable simulation of rate-coded and spiking neural networks on shared memory systems

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Abstract

The size and complexity of the neural networks investigated in computational neuroscience are increasing, leading to a need for efficient neural simulation tools to support their development. Several neuro-simulators have been developed over the years by the community, all with different scopes (rate-coded, spiking, mean-field), target platforms (CPU, GPU, clusters) or modeling principles (fixed model library, code generation). We compare here the current version of the neuro-simulator ANNarchy against other state-of-the-art simulators on ratecoded and spiking benchmarks with a focus on their parallel performance.

Publication
2019 Conference on Cognitive Computational Neuroscience, Berlin (Germany)