Neuromorphic Software Guide
Explore our curated collection of open source neuromorphic software resources.
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Neuromorphic Software
Explore Open Source Neuromorphic Software categorized by SNN Frameworks and Data Tools.
Built on top of PyTorch, used for simulating SNNs, geared towards ML and reinforcement learning.
- Website: https://bindsnet-docs.readthedocs.io/
- Source Code: https://github.com/bindsnet/bindsnet
- License: AGPL-3.0
Open-source DL framework for SNN based on PyTorch, with documentation in English and Chinese.
- Website: https://spikingjelly.readthedocs.io
- Source Code: https://github.com/fangwei123456/spikingjelly
- License: unknown
Focuses on gradient-based training of SNNs, based on PyTorch for GPU acceleration and gradient computation.
- Website: https://snntorch.readthedocs.io
- Source Code: https://github.com/jeshraghian/snntorch
- License: MIT
NIR SupportFree, open-source simulator for SNNs, written in Python, focusing on ease of use and flexibility.
- Website: https://briansimulator.org/
- Source Code: https://github.com/brian-team/brian2
- License: custom
Python package for building, testing, deploying neural networks, supporting many backends for SNN simulation.
- Website: https://nengo.ai
- Source Code: https://github.com/nengo/nengo
- License: custom
NIR Support Hardware SupportExploits bio-inspired neural components, sparse and event-driven, expands PyTorch with primitives for bio-inspired neural components.
- Website: https://norse.github.io/norse/
- Source Code: https://github.com/norse/norse
- License: LGPL-3.0
NIR SupportSimulator for SNN models focusing on dynamics, size, structure of neural systems, not on individual neuron morphology.
- Website: https://www.nest-simulator.org/
- Source Code: https://github.com/nest/nest-simulator
- License: GPL-2.0
Framework for developing neuro-inspired applications, mapping them to neuromorphic hardware.
- Website: https://lava-nc.org/
- Source Code: https://github.com/lava-nc/lava
- License: custom
NIR Support Hardware SupportSimulator for SNN models focusing on networks, not on individual neuron morphology. Optimised for accelerated simulations on computational backends including NVIDIA GPUs.
- Website: https://genn-team.github.io/
- Source Code: https://github.com/genn-team/genn
- License: LGPL-2.1
Tonic is a Python package for managing and transforming neuromorphic datasets.
- Website: https://tonic.readthedocs.io/
- Source Code: https://github.com/neuromorphs/tonic
- License: GPL-3.0
PyTorch-based DL library for SNNs, focusing on simplicity, fast training, extendability, and vision models.
- Website: https://sinabs.ai
- Source Code: https://github.com/synsense/sinabs
- License: AGPL-3.0
NIR Support Hardware SupportAEStream is a tool for transmitting event data efficiently, supporting diverse inputs/outputs and integrating with Python and C++ libraries.
- Website: https://aestream.github.io/aestream
- Source Code: https://github.com/aestream/aestream
- License: MIT
Machine learning library for SNN applications, supports GPU, TPU, CPU acceleration, and neuromorphic compute hardware deployment.
- Website: https://rockpool.ai
- Source Code: https://gitlab.com/synsense/rockpool
- License: AGPL-3.0
NIR Support Hardware SupportGPU-accelerated library for simulating large-scale spiking neural network (SNN) models with high biologically realistic synaptic dynamics.
- Website: https://uci-carl.github.io/CARLsim3/
- Source Code: https://github.com/UCI-CARL/CARLsim6
- License: MIT
Hardware SupportCompact SNN package on DeepMind's Haiku library, based on JAX for JIT compilation on GPUs and TPUs.
- Website: https://spyx.readthedocs.io
- Source Code: https://github.com/kmheckel/spyx
- License: MIT
NIR SupportA Python package to decode AEDAT 4 files from event cameras with a Rust implementation for speed.
- Website: https://pypi.org/project/aedat/
- Source Code: https://github.com/neuromorphicsystems/aedat
- License: MIT
Expelliarmus decodes event camera data into NumPy arrays, supporting various formats and offering ease of use for researchers and developers.
- Website: https://expelliarmus.readthedocs.io/
- Source Code: https://github.com/open-neuromorphic/expelliarmus
- License: GPL-2.0
Framework for machine learning with SNNs built on the GeNN simulator. Focused on ease of use in combination with computational efficiency derived from GeNN.
- Website: https://ml-genn.readthedocs.io/en/latest/
- Source Code: https://github.com/genn-team/ml_genn
- License: LGPL-2.1
