Brian2CUDA: Flexible and Efficient Simulation of Spiking Neural Network Models on GPUs.

ABSTRACT: Graphics processing units (GPUs) are widely available and have been used with great success to accelerate scientific computing in the last decade. These advances, however, are often not available to researchers interested in simulating spiking neural networks, but lacking the technical knowledge to write the necessary low-level code. Writing low-level code is not necessary when using the popular Brian simulator, which provides a framework to generate efficient CPU code from high-level model definitions in Python. Here, we present Brian2CUDA, an open-source software that extends the Brian simulator with a GPU backend. Our implementation generates efficient code for the numerical integration of neuronal states and for the propagation of synaptic events on GPUs, making use of their massively

SUBMITTER: Alevi D 

PROVIDER: S-EPMC9660315 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature