NVIDIA Clara AGX SDK 3.0 Goes Public and Includes New Application Container

The Clara AGX SDK runs on the NVIDIA Jetson and Clara AGX platform and provides developers with capabilities to build end-to-end streaming workflows for medical…

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NVIDIA
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Michael Zephyr
•2 min read•intermediate•
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PyTorchTensorFlowTransfer Learning

Overview

NVIDIA Clara AGX SDK 3.0 has been released, providing developers with tools to create end-to-end streaming workflows for medical imaging. This version includes support for NGC containers, new application containers, and updates to the Transfer Learning Toolkit.

What You'll Learn

1

How to utilize NGC containers with TensorFlow and PyTorch for medical imaging workflows

2

Why the new ultrasound application can enhance medical imaging capabilities

3

How to implement the latest Transfer Learning Toolkit (TLT) 3.0 for AI deployments

Prerequisites & Requirements

  • Familiarity with AI/ML frameworks like TensorFlow and PyTorch(optional)
  • Access to NVIDIA Clara AGX Development Kit

Key Questions Answered

What new features are included in NVIDIA Clara AGX SDK 3.0?
NVIDIA Clara AGX SDK 3.0 includes support for NGC containers with TensorFlow 1, TensorFlow 2, and PyTorch, along with three new application containers: Metagenomics, US4US Ultrasound, and Dermatology Melanoma detection. It also features updates to the Transfer Learning Toolkit (TLT) 3.0 for enhanced AI deployments.
How can developers access the Clara AGX SDK 3.0?
Developers can download Clara AGX SDK 3.0 from the Clara AGX Developer Site. An NVIDIA Developer Program account is required to access the SDK, and all containers can be found on the NGC platform.
What is the purpose of the new ultrasound application in the Clara AGX SDK?
The new ultrasound application in the Clara AGX SDK is designed to assist developers in building medical imaging workflows, providing sample code to facilitate integration and usage in AI medical devices.
What compatibility does the Transfer Learning Toolkit (TLT) 3.0 offer?
The Transfer Learning Toolkit (TLT) 3.0 offers compatibility with the DeepStream SDK, enabling developers to deploy real-time, low latency, high-resolution image AI applications effectively.

Technologies & Tools

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Software Development Kit
Nvidia Clara Agx SDK
Used for building end-to-end streaming workflows for medical imaging.
Machine Learning Framework
Tensorflow
Supported as part of the NGC containers for developing AI applications.
Machine Learning Framework
Pytorch
Supported as part of the NGC containers for developing AI applications.
Inference Server
Triton Inference Server
Facilitates model serving for AI applications.
Software Development Kit
Deepstream SDK
Used for real-time, low latency, high-resolution image AI deployments.

Key Actionable Insights

1
Leverage the new ultrasound application to streamline the development of medical imaging solutions.
This application provides sample code and resources that can significantly reduce the time and effort needed to implement ultrasound capabilities in AI medical devices.
2
Utilize the updated Transfer Learning Toolkit (TLT) 3.0 for optimizing AI models.
With TLT 3.0, developers can enhance their AI models for better performance in real-time applications, especially in medical imaging contexts.
3
Explore the NGC containers for rapid deployment of AI frameworks.
By using NGC containers, developers can quickly set up environments for TensorFlow and PyTorch, facilitating faster development cycles and reducing setup complexities.

Related Concepts

AI/ML Frameworks
Medical Imaging Technologies
Transfer Learning Toolkit