NVIDIA GPU-Optimized AMI
The NVIDIA GPU-Optimized AMI is a virtual machine image for accelerating your GPU accelerated Machine Learning, Deep Learning, Data Science and HPC workloads. Using this AMI, you can spin up a GPU-accelerated EC2 VM instance in minutes with a pre-installed Ubuntu OS, GPU driver, Docker and NVIDIA container toolkit.
This AMI provides easy access to NVIDIA's NGC Catalog, a hub for GPU-optimized software, for pulling & running performance-tuned, tested, and NVIDIA certified docker containers. The NGC catalog provides free access to containerized AI, Data Science, and HPC applications, pre-trained models, AI SDKs and other resources to enable data scientists, developers, and researchers to focus on building and deploying solutions.
This GPU-optimized AMI is free with an option to purchase enterprise support offered through NVIDIA AI Enterprise. For how to get support for this AMI, scroll down to 'Support Information'
Learn more
RoboMinder
Comprehensive monitoring, in-depth analysis, and interactive insights with our multimodal LLM-based analytics tool. Unify multi-modal data like video, logs, sensor data, and documentation for a complete operational overview. Delve beyond symptoms to uncover the deep causes of incidents, enabling preventative strategies and robust solutions. Dive into data with interactive inquiries to understand and learn from past incidents. Get early access to the next-gen of robot analytics.
Learn more
NVIDIA DIGITS
The NVIDIA Deep Learning GPU Training System (DIGITS) puts the power of deep learning into the hands of engineers and data scientists. DIGITS can be used to rapidly train the highly accurate deep neural network (DNNs) for image classification, segmentation and object detection tasks. DIGITS simplifies common deep learning tasks such as managing data, designing and training neural networks on multi-GPU systems, monitoring performance in real-time with advanced visualizations, and selecting the best performing model from the results browser for deployment. DIGITS is completely interactive so that data scientists can focus on designing and training networks rather than programming and debugging. Interactively train models using TensorFlow and visualize model architecture using TensorBoard. Integrate custom plug-ins for importing special data formats such as DICOM used in medical imaging.
Learn more
NVIDIA Holoscan
NVIDIA® Holoscan is a domain-agnostic AI computing platform that delivers the accelerated, full-stack infrastructure required for scalable, software-defined, and real-time processing of streaming data running at the edge or in the cloud. Holoscan supports a camera serial interface and front-end sensors for video capture, ultrasound research, data acquisition, and connection to legacy medical devices. Use the NVIDIA Holoscan SDK’s data transfer latency tool to measure complete, end-to-end latency for video processing applications. Access AI reference pipelines for radar, high-energy light sources, endoscopy, ultrasound, and other streaming video applications. NVIDIA Holoscan includes optimized libraries for network connectivity, data processing, and AI, as well as examples to create and run low-latency data-streaming applications using either C++, Python, or Graph Composer.
Learn more
