New paper on vectorised algorithms

We have a new paper in Neural Computation (in press) “Vectorised algorithms for spiking neural network simulation”, preprint available here. Abstract follows:

High-level languages (Matlab, Python) are popular in neuroscience because they are flexible and accelerate development. However, for simulating spiking neural networks, the cost of interpretation is a bottleneck. We describe a set of algorithms to simulate large spiking neural networks efficiently with high-level languages using vector-based operations. These algorithms constitute the core of Brian, a spiking neural network simulator written in the Python language. Vectorised simulation makes it possible to combine the flexibility of high-level languages with the computational efficiency usually associated with compiled languages.