CEVA Introduces Deep Learning in a Chip

8 October, 2015

Ceva Deep Neural Network (CDNN) enables embedded systems to perform deep learning tasks. "Our new technology is a first of its kind in the embedded industry"

“Our new Deep Neural Network framework for the CEVA-XM4 is the first of its kind in the embedded industry”

CEVA

CEVA, Inc. from Herzliya, Israel has revealed a ground breaking software framework to perform neural network deep learning task on its CEVA-XM4 DSP chip. The new Ceva Deep Neural Network (CDNN) enables embedded systems to perform deep learning tasks 3x faster than the leading GPU-based systems while consuming 30x less power and requiring 15x less memory bandwidth.

For example, running a Deep Neural Network (DNN) based pedestrian detection algorithm at 28nm requires less than 30mW for a 1080p 30 frames per second video stream. “Our new Deep Neural Network framework for the CEVA-XM4 is the first of its kind in the embedded industry,”  said Eran Briman, vice president of marketing at CEVA.

Key element in the solution is the CEVA Network Generator, a proprietary automated technology that converts a customer’s network structure and weights to a slim, customized network model used in real-time. This enables a faster network model which consumes significantly lower power and memory bandwidth, with less than 1% degradation in accuracy compared to the original network.

Eran Briman, vice president of marketing at CEVA
Eran Briman, vice president of marketing at CEVA

Phi Algorithm Solutions, from Toronto, Canada, has used CDNN to implement a CNN-based Universal Object Detector algorithm for the CEVA-XM4 DSP. This is now available for application developers and OEMs to run a variety of applications including pedestrian detection and face detection for security, ADAS and other embedded devices based around low-power camera-enabled systems.

The CDNN software framework is supplied as source code, extending the CEVA-XM4’s existing Application Developer Kit (ADK). It works with various networks and structures, such as Caffe, Torch or Theano training frameworks, or proprietary networks. CDNN includes real-time example models for image classification, localization and object recognition. For more information on CDNN: http://launch.ceva-dsp.com/cdnn.

CEVA is a leading licensor of DSP and IP platforms for cellular, multimedia and connectivity. Earlier this week the company announced that its revenues for the third quarter of 2015 are approximately $16.2 million, an all-time high, and above the high end of the Company’s previously revenue guidance of $15 to $16 million. As a result, its NASDAQ stock price rose from $18 to approximately $22. CEVA’s market cap jumped to $446 millions.

Tthe development board for CEVA-XM4
Tthe development board for CEVA-XM4
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