SuperNeuroMAT

The Super Speedy Spike Simulator.

SuperNeuroMAT is a Python package for simulating and analyzing spiking neural networks.

Documentation available: https://ORNL.github.io/superneuromat/

Unlike its sister package, SuperNeuroABM, SuperNeuroMAT uses a matrix-based representation of the network, which allows for more efficient simulation and GPU acceleration.

SuperNeuroMAT focuses on super-fast computation of Leaky Integrate and Fire (LIF) spiking neuron models with STDP.

It provides:

1. Support for leaky integrate and fire neuron model with the following parameters:

• neuron threshold
• neuron leak
• neuron refractory period

2. Support for Spiking-Time-Dependent Plasticity (STDP) on synapses with:

• weight
• delay
• per-synapse disabling of learning

3. Support for all-to-all connections as well as self connections
4. A turing-complete model of neuromorphic computing
5. Optional GPU acceleration or Optional Sparse computation

• Note that long delays may impact performance. Consider using an agent-based simulator such as SuperNeuroABM for longer delays.

Installation

1. Install using pip install superneuromat
2. Update/upgrade using pip install superneuromat --upgrade

The installation guide covers virtual environments, faster installation with uv, installing support for CUDA GPU acceleration, and more.

Usage

Import the spiking neural network class:

from superneuromat import SNN

See the tutorial for more.

Additionally, the migration guide may be of use to those coming from older versions of SuperNeuroMAT.

Citation

1. Please cite SuperNeuroMAT using:

   @inproceedings{date2023superneuro,
     title={SuperNeuro: A fast and scalable simulator for neuromorphic computing},
     author={Date, Prasanna and Gunaratne, Chathika and R. Kulkarni, Shruti and Patton, Robert and Coletti, Mark and Potok, Thomas},
     booktitle={Proceedings of the 2023 International Conference on Neuromorphic Systems},
     pages={1--4},
     year={2023}
   }
   

2. References for SuperNeuroMAT:
   • SuperNeuro: A Fast and Scalable Simulator for Neuromorphic Computing
   • Neuromorphic Computing is Turing-Complete
   • Computational Complexity of Neuromorphic Algorithms