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GTC On-Demand

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Abstract:
We'll present a fast, highly accurate, and customizable object-detection network optimized for training and inference on GPUs. After describing the network architecture, we'll dive into how different stages of training workflow are accelerated. Our techniques include data ingestion and augmentation, mixed precision, and multi-GPU training. We'll demonstrate how we optimized our network for deployment without loss of accuracy using ONNX and NVIDIA TensorRT. We'll also show how to create TensorRT plugins for post-processing to perform inference entirely on the GPU. This session will be a combination of lecture and demos.
We'll present a fast, highly accurate, and customizable object-detection network optimized for training and inference on GPUs. After describing the network architecture, we'll dive into how different stages of training workflow are accelerated. Our techniques include data ingestion and augmentation, mixed precision, and multi-GPU training. We'll demonstrate how we optimized our network for deployment without loss of accuracy using ONNX and NVIDIA TensorRT. We'll also show how to create TensorRT plugins for post-processing to perform inference entirely on the GPU. This session will be a combination of lecture and demos.  Back
 
Topics:
AI Application Deployment and Inference, Deep Learning and AI Frameworks, Computer Vision
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9243
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