kopyasnn

kopyasnn is an open-source software framework for developing and deploying spiking neural networks (SNNs) and related neuromorphic computing applications. The project provides tools for simulation, training, and deployment across conventional computing hardware and neuromorphic backends.

Origin and governance: kopyasnn originated from collaborative projects among researchers in machine learning and computational neuroscience during the late 2010s. It is maintained by an international community of contributors and hosted on a public code repository, with governance focused on transparency and open collaboration.

Architecture and capabilities: The framework offers a modular architecture with neuron models such as leaky integrate-and-fire (LIF) and its variants, and supports learning rules including surrogate-gradient-based backpropagation and spike-timing-dependent plasticity (STDP). It provides a Python API, data loading utilities, and utilities for building network topologies. kopyasnn can run simulations on CPUs and GPUs and can target neuromorphic hardware via backend backends. It includes tools for model conversion, benchmarking, and visualization.

Applications and reception: Researchers use kopyasnn for sensory processing, pattern recognition, robotics, and time-series analysis. It is cited in education and experimentation with SNNs. The project is noted for its emphasis on accessibility and interoperability, though users report a learning curve and variability in performance depending on hardware and configuration.

Licensing and availability: kopyasnn is released under the MIT license and maintained with open-source development practices. The project is distributed through its official repository and documentation, which include tutorials and examples.