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GTC On-Demand

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Abstract:
Learn how to bring the power of convolutional neural networks and deep learning to memory- and power-constrained devices like smartphones, wearable devices, and drones. We'll show these techniques at work on real-world project and discuss tips and tricks, speed and accuracy trade-offs, and benchmarks on different hardware. We will then demonstrate how to get started developing your own deep learning application for storage- and power-constrained mobile devices. We'll also discuss how to apply similar techniques to increase deep neural net efficiency when deploying in a regular cloud-based production environment. This approach reduces the number of GPUs required and lowers cost.
Learn how to bring the power of convolutional neural networks and deep learning to memory- and power-constrained devices like smartphones, wearable devices, and drones. We'll show these techniques at work on real-world project and discuss tips and tricks, speed and accuracy trade-offs, and benchmarks on different hardware. We will then demonstrate how to get started developing your own deep learning application for storage- and power-constrained mobile devices. We'll also discuss how to apply similar techniques to increase deep neural net efficiency when deploying in a regular cloud-based production environment. This approach reduces the number of GPUs required and lowers cost.  Back
 
Topics:
AI Application Deployment and Inference, AI and DL Research
Type:
Tutorial
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9648
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