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our_knp/examples/CHANGELOG.md
int 8f43927575 Initial import: KNP experiments (examples, viz, cats-dogs, reports) 
examples/ is based on KasperskyLab/knp at 55470ed6 with local changes
to the mnist-learn altai/blifat models, cuda-backend CMake and model_loader.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-14 18:17:15 +03:00

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Kaspersky Neuromorphic Platform changelog

Release for Kaspersky Neuromorphic Platform 2.0 - 2025-12

Changes

  • Distribution kit for developing Linux applications: added packages containing a backend library for GPUs with CUDA support technology.
  • Backends:
    • CUDABackend: added an interface for the GPU backend.
    • SingleThreadedCPUBackend backend: added neuron support based on the AltAILIF model.
    • MultiThreadedCPUBackend backend: added neuron support based on the SynapticResourceSTDPBLIFATNeuron model and synapse based on the SynapticResourceSTDPDeltaSynapse model.
    • Optimized CPU backend operation.
  • C++ components:
    • core library: extended the functionality for the Backend, MessageBus, MessageEndpoint, Population, Projection, Subscription, and TagMap classes.
    • Framework for C ++: extended the functionality of the C++ framework:
      • data_processing namespace: added a namespace that provides functionality for processing classification model training and testing data.
      • inference_evaluation namespace: added a namespace that provides functionality for evaluating model quality.
      • modifier namespace: added a namespace that provides message handlers.
      • normalization namespace: added a namespace that provides functions and functors for normalizing the parameters of neurons and synapses in neural networks.
      • monitoring namespace: added the model namespace with model monitoring functions.
      • projection namespace: added functions to generate synapses and synapse projections.
      • ModelExecutor class: added methods.
    • neuron_traits library: extended the neuron interfaces for the BLIFATNeuron and SynapticResourceSTDPBLIFATNeuron models.
  • Components for use in Python: added methods for the ModelExecutor and UID classes.
  • synapse_traits library (for use in C++ and Python): extended the interface of the synapse based on the SynapticResourceSTDPDeltaSynapse model.
  • Example mnist-learn is an added example of training a neural network on images of handwritten numbers and their labels from the MNIST database and its execution.

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