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

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.