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GTC On-Demand

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Abstract:
You may already use NVIDIA's cuDNN library to accelerate your deep neural network inference, but are you getting the most out of it to truly unleash the tremendous performance of NVIDIA's newest GPU architectures, Volta and Turing? We'll discuss how to avoid the most common pitfalls in porting your CPU-based inference to the GPU and demonstrate best practices in a step-by-step optimization of an example network. Learn how to deploy your deep neural network inference in both the fastest and most memory-efficient way, using cuDNN and Tensor Cores, NVIDIA's revolutionary technology that delivers groundbreaking performance in FP16, INT8 and INT4 inference on Volta and Turing.
You may already use NVIDIA's cuDNN library to accelerate your deep neural network inference, but are you getting the most out of it to truly unleash the tremendous performance of NVIDIA's newest GPU architectures, Volta and Turing? We'll discuss how to avoid the most common pitfalls in porting your CPU-based inference to the GPU and demonstrate best practices in a step-by-step optimization of an example network. Learn how to deploy your deep neural network inference in both the fastest and most memory-efficient way, using cuDNN and Tensor Cores, NVIDIA's revolutionary technology that delivers groundbreaking performance in FP16, INT8 and INT4 inference on Volta and Turing.  Back
 
Topics:
AI Application Deployment and Inference, Deep Learning and AI Frameworks
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9644
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Abstract:
We'll show how a headset-mounted depth camera can be used to enable scalable real-time scene reconstruction for immersive mixed reality applications. We'll discuss and profile optimized CUDA kernels that leverage the tremendous performance of an NVIDIA Quadro GP100. Furthermore, we'll show how knowledge of the headset's position and orientation in space can be leveraged to improve and make more robust the reconstruction process.
We'll show how a headset-mounted depth camera can be used to enable scalable real-time scene reconstruction for immersive mixed reality applications. We'll discuss and profile optimized CUDA kernels that leverage the tremendous performance of an NVIDIA Quadro GP100. Furthermore, we'll show how knowledge of the headset's position and orientation in space can be leveraged to improve and make more robust the reconstruction process.  Back
 
Topics:
Performance Optimization, Virtual Reality and Augmented Reality
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8698
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