SEARCH SESSIONS

Search All
 
Refine Results:
 
Year(s)

SOCIAL MEDIA

EMAIL SUBSCRIPTION

 
 

GTC ON-DEMAND

Presentation
Media
Abstract:

Take a journey through the TensorFlow container provided by the NVIDIA GPU Cloud. We'll start with how to launch and navigate inside the container, and stop along the way to explore the included demo scripts, extend the container with extra software, and examine best practices for how to take advantage of all the benefits bundled inside the NGC TensorFlow container. This session will help NGC beginners get the most out of the TensorFlow container and become productive as quickly as possible.

Take a journey through the TensorFlow container provided by the NVIDIA GPU Cloud. We'll start with how to launch and navigate inside the container, and stop along the way to explore the included demo scripts, extend the container with extra software, and examine best practices for how to take advantage of all the benefits bundled inside the NGC TensorFlow container. This session will help NGC beginners get the most out of the TensorFlow container and become productive as quickly as possible.

  Back
 
Topics:
AI Application, Deployment & Inference, Deep Learning & AI Frameworks
Type:
Tutorial
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9256
Download:
Share:
 
Abstract:
Learn how you can utilize TensorRT and NVIDIA Docker to quickly configure and deploy a GPU-accelerated inference server and start gaining insights from your trained deep neural network (DNN) models. TensorRT is a high-performance tool for low-latency, high-throughput DNN inference. The latest release of TensorRT introduces a novel, framework-agnostic network definition format called universal framework format, which allows TensorRT to support and optimize DNN models trained in multiple deep learning frameworks. We'll leverage the TensorRT Python API to create a lightweight Python Flask application capable of serving multiple DNN models trained using TensorFlow, PyTorch, and Caffe, and also discuss how to containerize this inference service using NVIDIA Docker for ease of deployment at scale. This session will consist of a lecture, live demos, and detailed instructions.
Learn how you can utilize TensorRT and NVIDIA Docker to quickly configure and deploy a GPU-accelerated inference server and start gaining insights from your trained deep neural network (DNN) models. TensorRT is a high-performance tool for low-latency, high-throughput DNN inference. The latest release of TensorRT introduces a novel, framework-agnostic network definition format called universal framework format, which allows TensorRT to support and optimize DNN models trained in multiple deep learning frameworks. We'll leverage the TensorRT Python API to create a lightweight Python Flask application capable of serving multiple DNN models trained using TensorFlow, PyTorch, and Caffe, and also discuss how to containerize this inference service using NVIDIA Docker for ease of deployment at scale. This session will consist of a lecture, live demos, and detailed instructions.  Back
 
Topics:
AI Application, Deployment & Inference, Tools & Libraries, Data Center & Cloud Infrastructure
Type:
Tutorial
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8495
Streaming:
Download:
Share:
 
Abstract:
We'll present results on speeding up Bayesian inference in NVIDIA DGX-1 server for medical diagnostics. Bayesian inference is an AI technique to reason under uncertainty that is computationally and data intensive. We'll discuss the implications for both inference and training of Bayesian networks.
We'll present results on speeding up Bayesian inference in NVIDIA DGX-1 server for medical diagnostics. Bayesian inference is an AI technique to reason under uncertainty that is computationally and data intensive. We'll discuss the implications for both inference and training of Bayesian networks.  Back
 
Topics:
AI Application, Deployment & Inference, Accelerated Data Science
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8488
Streaming:
Share:
 
Abstract:
Spin up a deep learning (DL) proof-of-concept on a budget. We'll walk you through a DL workflow in the cloud leveraging DIGITS, then download a trained model, and run inference on a Jetson TX2. This session considers multiple options such as Nimbix, AMI, and NGC on Tesla P100, Tesla V100, and NVIDIA DGX-1 servers. This tutorial will be a combination of lecture, live demos, and detailed instructions.
Spin up a deep learning (DL) proof-of-concept on a budget. We'll walk you through a DL workflow in the cloud leveraging DIGITS, then download a trained model, and run inference on a Jetson TX2. This session considers multiple options such as Nimbix, AMI, and NGC on Tesla P100, Tesla V100, and NVIDIA DGX-1 servers. This tutorial will be a combination of lecture, live demos, and detailed instructions.  Back
 
Topics:
AI & Deep Learning Research, Accelerated Data Science
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8286
Download:
Share: