The Akida Neuromorphic ML Framework

The Akida Development Environment (MetaTF) is a complete machine learning framework enabling the seamless creation, training, and testing of neural networks on the Akida Neuromorphic Processor Platform. MetaTF includes an Akida Neuromorphic Processor IP simulator for execution of models in addition to Akida hardware implementations such as the AKD1000 reference SoC.
Inspired by the Keras API, MetaTF provides a high-level Python API for neural networks. This API facilitates early evaluation, design, final tuning, and productization of neural network models.

AKD1000 reference SoC (left), Akida 2nd Generation IP (right)

MetaTF is comprised of four Python packages which leverage the TensorFlow framework and are installed from the PyPI repository via pip command.
The four MetaTF packages contain:
  • a Model zoo (akida-models) to directly load quantized models or to easily instantiate and train Akida compatible models,

  • a quantization tool (quantizeml) for quantization of CNN and Vision Transformer models using low-bitwidth weights and outputs,

  • a conversion tool (cnn2snn) to convert models to a binary format for model execution on an Akida platform,

  • and an interface to the Akida Neuromorphic Processor (akida) including a runtime, a Hardware Abstraction Layer (HAL) and a software backend. It allows the simulation of the Akida Neuromorphic Processor and use of the AKD1000 reference SoC.


Akida MetaTF ML Framework

The Akida package introduced above allows one to simulate the Akida Neuromorphic Processor IP without the need for any hardware. Furthermore, the interface to the Akida runtime enables seamless integration with Python-based, machine learning frameworks for easy prototyping with the Akida Neuromorphic Processor IP.
It includes:
  • the Akida model API - a library supporting the native development of Akida models, the inference of instantiated models, their serialization (program sequences) and their mapping for a targeted hardware device,

  • a simulator (software backend) - a CPU implementation of the Akida Neuromorphic Processor IP,

  • and the Akida Engine Library - a C++ library supporting the instantiation of model programs produced by the model library on actual hardware devices and inference on programmed devices.


Akida runtime configurations

The Akida examples

The examples section includes tutorials and examples to easily get started with Akida technology. This section illustrates the use of Akida technology on a variety of inference and incremental, on-device learning applications.


While the Akida examples are provided under an Apache License 2.0, the underlying Akida library is proprietary.
Please refer to the End User License Agreement for terms and conditions.