The CEVA-CDNN is a comprehensive toolkit that simplifies the development and deployment of deep learning systems for mass-market embedded devices. Tailored and optimized for the CEVA-XM family of imaging and vision DSPs, the CDNN toolkit includes the CEVA network generator, the CDNN software framework, and a CNN hardware accelerator that work together to deliver superior performance while ensuring flexibility with the constantly evolving requirements of machine learning.

The CDNN software framework enable an extremely simple and streamlined transition of existing deep neural networks to an embedded environment. NeuPro AI processor ensure superior performance with minimal power consumption. Separately, each component of the CDNN toolkit is a powerful enabler of embedded imaging and vision applications. Combined, these pieces deliver an ultimate toolkit to support new network structures and changing layer types of deep neural networks.

CEVA supplies a full development platform for partners and developers based on the CEVA-XM family of DSP cores to enable the development of deep learning applications using the CDNN, targeting any advanced network.



The CDNN toolkit streamlines implementations of deep learning in embedded systems by automatically converting offline pre-trained neural networks to real-time embedded-ready networks for CEVA-XM cores and CEVA-NeuPro AI processors, using the CEVA Network Generator. This enables real-time, high-quality image classification, object recognition, and vision analytics.

Automatic conversion to embedded-ready networks
Supports a wide variety of neural network structures, including any number and type of layers of deep neural networks
Powerful hardware accelerators maximize processing throughput

Main Features

  • The CEVA Network Generator converts pre-trained neural network models and weights from offline training frameworks (such as Caffe or TensorFlow) to a real-time network model.
  • The CDNN second-generation neural network software framework accelerates deployment of machine learning in low-power embedded systems.
  • Coupled with the CEVA-XM family of intelligent vision processors and CEVA-NeuPro AI processors, the CDNN offers significant time-to-market and power advantages for implementing machine learning in embedded systems.

CEVA CDNN live demonstration

CDNN is CEVA’s 3rd Generation Neural Network Software Framework for Machine Learning that supports Artificial Intelligence Including Google’s TensorFlow
CDNN enables localized, deep learning-based video analytics on camera devices in real time. Coupled with the CEVA-XM intelligent vision processor family and CEVA-NeuPro AI Processors, CDNN offers significant time-to-market and power advantages for implementing machine learning in embedded systems for smartphones, advanced driver assistance systems (ADAS), surveillance equipment, drones, robots and other camera-enabled smart devices.
In this video clip we demonstrate how a pre-trained neural network (“Age Classification”, can be found here: http://www.openu.ac.il/home/hassner/p…) is downloaded from the internet, converted to an embedded-friendly network, and runs on the CEVA-XM4 FPGA platform in less than 10 mins!