Press Release Summary:
The CEVA Deep Neural Network Compiler now improves the capabilities of CEVA-XM and NeuPro customers and ecosystem partners to train and enrich neural network-based applications. The compiler allows developers to import models generated using ONNX-compatible framework and use them on CEVA-XM vision DSPs and NeuPro AI processors.
Original Press Release:
CEVA Adds ONNX Support to CDNN Neural Network Compiler
Open Neural Network Exchange (ONNX) support in latest CDNN release enables neural networks trained in various deep learning frameworks to be seamlessly deployed on CEVA-XM Vision DSPs and NeuPro AI processors
MOUNTAIN VIEW, Calif., – October 24, 2018 – CEVA, Inc. (NASDAQ: CEVA), the leading licensor of signal processing platforms and artificial intelligence processors for smarter, connected devices, today announced that the latest release of its award-winning CEVA Deep Neural Network (CDNN) compiler supports the Open Neural Network Exchange (ONNX) format.
"CEVA is fully committed to ensuring an open, interoperable AI ecosystem, where AI application developers can take advantage of the features and ease-of-use of the various deep learning frameworks most suitable to their specific use case,” said Ilan Yona, vice president and general manager of CEVA's Vision Business Unit. “By adding ONNX support to our CDNN compiler technology, we provide our CEVA-XM and NeuPro customers and ecosystem partners with much broader capabilities to train and enrich their neural network-based applications.”
ONNX is an open format created by Facebook, Microsoft and AWS to enable interoperability and portability within the AI community, allowing developers to use the right combinations of tools for their project, without being ‘locked in’ to any one framework or ecosystem. The ONNX standard ensures interoperability between different deep learning frameworks, giving developers complete freedom to train their neural networks using any machine learning framework and then deploy it using another AI framework. Now with support for ONNX, CDNN enables developers to import models generated using any ONNX-compatible framework, and deploy them on the CEVA-XM vision DSPs and NeuPro AI processors.
The CEVA Deep Neural Network (CDNN) is a comprehensive compiler technology that creates fully-optimized runtime software for CEVA-XM Vision DSPs and NeuPro AI processors. Targeted for mass-market embedded devices, CDNN incorporates a broad range of network optimizations, advanced quantization algorithms, data flow management and fully-optimized compute CNN and RNN libraries into a holistic solution that enables cloud-trained AI models to be deployed on edge devices for inference processing.
CEVA supplies a full development platform for partners and developers based on the CEVA-XM and NeuPro architectures to enable the development of deep learning applications using the CDNN, targeting any advanced network. For more information, please visit https://www.ceva-dsp.com/product/ceva-deep-neural-network-cdnn/.
About CEVA, Inc.
CEVA is the leading licensor of signal processing platforms and artificial intelligence processors for a smarter, connected world. We partner with semiconductor companies and OEMs worldwide to create power-efficient, intelligent and connected devices for a range of end markets, including mobile, consumer, automotive, industrial and IoT. Our ultra-low-power IPs for vision, audio, communications and connectivity include comprehensive DSP-based platforms for LTE/LTE-A/5G baseband processing in handsets, infrastructure and cellular IoT enabled devices, advanced imaging and computer vision for any camera-enabled device, audio/voice/speech and ultra-low power always-on/sensing applications for multiple IoT markets. For artificial intelligence, we offer a family of AI processors capable of handling the complete gamut of neural network workloads, on-device. For connectivity, we offer the industry’s most widely adopted IPs for Bluetooth (low energy and dual mode) and Wi-Fi (Wi-Fi 4 (802.11n), Wi-Fi 5 (802.11ac) and Wi-Fi 6 (802.11ax) up to 4x4). Visit us at www.ceva-dsp.com and follow us on Twitter, YouTube and LinkedIn.
For more information, contact:
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