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@uci.edu http://www.socsci.uci.edu/~jkrichma