CARLsim

GPU-accelerated library for simulating large-scale spiking neural network (SNN) models with high biologically realistic synaptic dynamics.

Overview

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 a PyNN-like programming interface in C/C++, which allows for details and parameters to be specified at the synapse, neuron, and network level.

Some features include:

  • CUDA 11 support
  • CMake build system
  • Neuromodulatory features
  • Integration of Python LEAP
  • Axonal Plasticity learning rule (release 6.1)
  • a more complete STDP implementation which includes neuromodulatory mechanisms
  • an automated parameter tuning interface that utilizes evolutionary algorithms to construct functional SNNs
  • a test suite for functional code verification

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