Connectionists: Release of CARLsim5 - Latest version of our GPU-accelerated Spiking Neural Network Simulator

[Jeffrey Krichmar]

Dear Colleagues,

We are pleased to announce the release of CARLsim5. CARLsim is an efficient, easy-to-use, GPU-accelerated library for simulating large-scale spiking neural network (SNN) models with a high degree of biological detail. CARLsim allows execution of networks of Izhikevich spiking neurons with realistic synaptic dynamics on both generic x86 CPUs and standard off-the-shelf GPUs. The simulator provides an intuitive programming interface in C/C++, which allows for details and parameters to be specified at the synapse, neuron, and network level. The new release has a python frontend that is compatible with PyNN.

Software and user documentation can be found at:  https://github.com/UCI-CARL/CARLsim5

New and improved features in CARLsim5 include:
·     PyNN compatibility
·     Neuron monitor for observing the voltage and current traces of individual neurons
·     Improved installation for the Evolutionary Computations in Java (ECJ) interface (coming soon)
·     Docker images for Windows users and computer cluster users
·     Saving and loading simulations

For those interested in the pyCARL interface, our IJCNN paper will be presented at the Plenary Poster Session I-P7: Spiking Neural Networks, Tuesday, July 21, 2:30PM-4:30PM GMT+1), IJCNN Poster Room 1: P1317 PyCARL: A PyNN Interface for Hardware-Software Co-Simulation of Spiking Neural Network [#20903]

Sincerely,

The CARLsim team

Jeff Krichmar
Department of Cognitive Sciences
2328 Social & Behavioral Sciences Gateway
University of California, Irvine
Irvine, CA 92697-5100
jkrichma at uci.edu
http://www.socsci.uci.edu/~jkrichma