Spiking Neural Network (SNN) Frameworks
Discover essential SNN frameworks for neuromorphic software development.
Open-source DL framework for SNN based on PyTorch, with documentation in English and Chinese.
Maintained by
Wei Fang
Focuses on gradient-based training of SNNs, based on PyTorch for GPU acceleration and gradient computation.
Maintained by
NIR SupportView DetailsBuilt on top of PyTorch, used for simulating SNNs, geared towards ML and reinforcement learning.
Maintained by
Free, open-source simulator for SNNs, written in Python, focusing on ease of use and flexibility.
Maintained by
Romain Brette, Marcel Stimberg, Dan Goodman
Python package for building, testing, deploying neural networks, supporting many backends for SNN simulation.
Maintained by
NIR Support Hardware SupportView DetailsExploits bio-inspired neural components, sparse and event-driven, expands PyTorch with primitives for bio-inspired neural components.
Maintained by
NIR SupportView DetailsFramework for developing neuro-inspired applications, mapping them to neuromorphic hardware.
Maintained by
Intel NC team
NIR Support Hardware SupportView DetailsSimulator for SNN models focusing on dynamics, size, structure of neural systems, not on individual neuron morphology.
Maintained by
Jochen Martin Eppler
Simulator for SNN models focusing on networks, not on individual neuron morphology. Optimised for accelerated simulations on computational backends including NVIDIA GPUs.
Maintained by
Compact SNN package on DeepMind's Haiku library, based on JAX for JIT compilation on GPUs and TPUs.
Maintained by
NIR SupportView DetailsPyTorch-based DL library for SNNs, focusing on simplicity, fast training, extendability, and vision models.
Maintained by
Sadique Sheik
NIR Support Hardware SupportView DetailsGPU-accelerated library for simulating large-scale spiking neural network (SNN) models with high biologically realistic synaptic dynamics.
Maintained by
Jeff Krichmar
Hardware SupportView DetailsFramework for machine learning with SNNs built on the GeNN simulator. Focused on ease of use in combination with computational efficiency derived from GeNN.
Maintained by
A platform for creating and training Spiking Neural Networks (SNNs), supporting various data types and neuromorphic processors.
Maintained by
Kaspersky
Hardware SupportView DetailsEvent-based training of spiking neural networks with support for BrainScaleS-2 hardware-in-the-loop based on JAX.
Maintained by
Electronic Visions Group
NIR Support Hardware SupportView DetailsA PyTorch extension for the Neuromorphic Intermediate Representation (NIR), enabling seamless conversion of PyTorch-based SNN models to and from NIR.
Maintained by
NIR Support Hardware SupportView DetailsMachine learning library for SNN applications, supports GPU, TPU, CPU acceleration, and neuromorphic compute hardware deployment.
Maintained by
NIR Support Hardware SupportView DetailsTraining spiking neural networks with BrainScaleS-2 hardware-in-the-loop support based on PyTorch.
Maintained by
Electronic Visions Group
NIR Support Hardware SupportView DetailsSpiking neural networks with complex plasticity on BrainScaleS-2 neuromorphic hardware.
Maintained by
Electronic Visions Group
Hardware SupportView Details
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