Clara AGX Container is a software platform that allows programmers to create and operate machine learning models, emphasizing medical applications. The platform provides access to Nvidia's Clara AGX computational resources, which can be used to train and operate machine learning algorithms on high-performance graphics processing units (GPUs).
A container technology that allows you to run applications within containers. Think of it as a file cabinet for your software: Each application lives within its own container, but all the containers can be accessed together in a single interface. This makes it easier to find and manage your software.
Benefits of using CLARA AGX
The benefits of using Clara AGX are numerous. This product is designed for medical professionals and programmers and hospitals, and medical research organizations. It offers the following benefits:
- Increased security
Applications running within containers cannot interfere with each other or the operating system outside of them, so the risk of data breaches is significantly reduced.
- Increased mobility
Because they are isolated from the host environment and can run anywhere, Docker runs (including Windows, Linux, and MacOS), containers offer more flexibility than traditional virtual machines when moving between different environments.
- Increased scalability
Containers can scale up or down based on demand as well as across multiple platforms simultaneously—allowing organizations to easily match their infrastructure needs with fluctuating levels of business activity.
About Clara AGX container
With an increase in demand for AI products and services, high-performance GPUs are becoming more and more necessary. However, AGXs are difficult to maintain on their own. Clara AGX containers allow you to take advantage of GPU resources without the hassle of using your own server.
Clara AGX containers are designed so that they can be easily plugged into your existing cloud deployment, which means you can start using them right away without having to migrate anything. They also support a wide range of applications, so there's likely a Clara container that meets your needs no matter what kind of work you're doing.
The container is GPU-enabled, but it can also run inference on the CPU. When you build your application with Clara AGX, you can deploy it to various platforms. Clara AGX supports both hybrid and heterogeneous environments. That means your application can use the optimal hardware for each task.
Clara AGX was built to give developers the ability to execute deep learning models in real-time, with high performance and low latency. It's not just for autonomous vehicles anymore. Clara AGX is used in a wide range of industries, from healthcare to content creation and other applications like image analysis and video processing.
Clara AGX Container is a container-based deployment of Clara Train, which allows you to train and deploy AI applications on your data. It provides state-of-the-art algorithms for training and deploying AI.
Features of Clara AGX Container
The Clara AGX Container has the following features:
- Contains Intel Optimization for TensorFlow
- Supports TensorBoard, Jupyter Notebook, and SSH
- Securely accesses the container using an authentication key pair
- Provides a Docker image that contains all the needed libraries for running AI applications
- It has an optional GPU container to get started with its use
- Allows you to train and deploy AI models without having to install anything on your development system.
- Automated model training and inference pipelines
- Object detection, image classification, semantic segmentation and more
- Intuitive dashboards with real-time visualization of model training and inference
Clara AGX provides a flexible way for you to deploy and manage your NVIDIA AI applications. By combining the power of GPUs and deep learning with the flexibility of containers, Clara AGX is designed to optimize workflows across the AI life cycle.
Nvidia GPU Container supports popular machine learning frameworks such as TensorFlow, Caffe, PyTorch, MXNet, Chainer, Microsoft Cognitive Toolkit (CNTK), Theano and Keras on NVIDIA DGX Systems, NVIDIA TITAN GPUs and NVIDIA Tesla GPUs.
Clara AGX is an accelerated computing platform powered by NVIDIA RTX GPUs, which are designed to handle complex AI and HPC workloads on edge devices. Clara AGX can be used to run or deploy NGC containers, which can help streamline the process of building models for deployment in health care and other industries.
NVIDIA provides two types of containers
Containers that provide a complete software stack including drivers, software libraries and tools required to run an application. These containers can be run on NVIDIA GPUs or CPU-only systems with NVIDIA drivers installed. Each container contains CUDA drivers and a CUDA toolkit.
Containers that contain only the NVIDIA kernel driver and CUDA libraries are required to run an application. These containers require a full OS image to run the application. NVIDIA driver container consists of NVIDIA-driver, CUDA toolkit, CUDNN and NVIDIA container runtime (NVIDIA runtime).
With this, you will be able to more easily deploy a unified AI/ML workflow that is portable across any platform. This means you can use it for training, inferencing, and simulation.
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