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Abstract:

Todays Internet of Things (IoT) has evolved into the Internet of Experiences where autonomous products and connected devices are integrating more and more software to digitally connect to the physical world around them, blending together to become part of a living experience shaped by interactions between products, nature and life. To make them seamlessly work together, industrial companies, along with their ecosystem, are looking for the ability to virtually co-design and simulate systems of systems, embedded systems and software architectures across industries, shorten design and engineering innovation cycles through automation and systematic reuse of existing data lakes for the training of Cognitive Augmented Companions. 3DEXPERIENCE CATIA is operating the shift from traditional Computer Aided Design towards Cognitive Augmented Design where a seamless collaboration between engineers and AI-powered Design solutions empower our users with Know How reaching far beyond their initial domain of expertise.  Combined with Systems Engineering solutions, this paradigm shift enables organizations to first focus on the challenges to solve and then to quickly and easily evaluate requests for new system variants, that reduces the overall development cost thanks to an open and extensible development platform a platform that fully integrates cross-discipline modeling, simulation, verification and business process support needed for developing simple to sophisticated cyber-physical systems.  In this presentation, we will illustrate how the Cognitive Augmented solutions could support engineers to design GPU enabled intelligent systems while relying themselves on the use of AIs powered by accelerated computing.

Todays Internet of Things (IoT) has evolved into the Internet of Experiences where autonomous products and connected devices are integrating more and more software to digitally connect to the physical world around them, blending together to become part of a living experience shaped by interactions between products, nature and life. To make them seamlessly work together, industrial companies, along with their ecosystem, are looking for the ability to virtually co-design and simulate systems of systems, embedded systems and software architectures across industries, shorten design and engineering innovation cycles through automation and systematic reuse of existing data lakes for the training of Cognitive Augmented Companions. 3DEXPERIENCE CATIA is operating the shift from traditional Computer Aided Design towards Cognitive Augmented Design where a seamless collaboration between engineers and AI-powered Design solutions empower our users with Know How reaching far beyond their initial domain of expertise.  Combined with Systems Engineering solutions, this paradigm shift enables organizations to first focus on the challenges to solve and then to quickly and easily evaluate requests for new system variants, that reduces the overall development cost thanks to an open and extensible development platform a platform that fully integrates cross-discipline modeling, simulation, verification and business process support needed for developing simple to sophisticated cyber-physical systems.  In this presentation, we will illustrate how the Cognitive Augmented solutions could support engineers to design GPU enabled intelligent systems while relying themselves on the use of AIs powered by accelerated computing.

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Topics:
Computer Aided Engineering, Product & Building Design, Additive Manufacturing, Digital Product Design & Styling
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S91032
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Abstract:
One of the tough aspect of Deep Neural Network resides in its behavior validation. Although actual driving should be achieved with physical cars to train the neural network, there is today no tool to appropriately prepare data acquisition campaign or go through stress validation before further on-road testing and industrial deployment. This talk will show how hardware and software in the loop on 3DEXPERIENCE CATIA, can now be extended to AI in the loop, with the ability to activate the full system engineering simulation with the actual neural network meant to run in the autonomous vehicle, accurately reproducing the neural network inference and checking overall vehicle behavior in various conditions. Every stage from full 3D synthetic data ingest and real-time software simulation, through actual hardware in the loop validation both use cases leveraging TensorRT GPU inference can now consistently be proofed for appropriate in-depth understanding of the network reactions before it drives on the road. A POC showing TensorRT and DNN behavior validation will be presented in details, opening new opportunities to validate GPU inference but also compare actual performance impact versus CPU
One of the tough aspect of Deep Neural Network resides in its behavior validation. Although actual driving should be achieved with physical cars to train the neural network, there is today no tool to appropriately prepare data acquisition campaign or go through stress validation before further on-road testing and industrial deployment. This talk will show how hardware and software in the loop on 3DEXPERIENCE CATIA, can now be extended to AI in the loop, with the ability to activate the full system engineering simulation with the actual neural network meant to run in the autonomous vehicle, accurately reproducing the neural network inference and checking overall vehicle behavior in various conditions. Every stage from full 3D synthetic data ingest and real-time software simulation, through actual hardware in the loop validation both use cases leveraging TensorRT GPU inference can now consistently be proofed for appropriate in-depth understanding of the network reactions before it drives on the road. A POC showing TensorRT and DNN behavior validation will be presented in details, opening new opportunities to validate GPU inference but also compare actual performance impact versus CPU  Back
 
Topics:
AI Application Deployment and Inference, Product & Building Design
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8748
Streaming:
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