What's better than a giant room full of computers learning how to solve your problems? A giant room of computers all supplemented with GPUs to speed up those calculations. They're not just for games, anymore; GPUs are quickly becoming essential hardware for high performance computing and for cluster-based applications that crunch lots of numbers.
On November 10, 11 AM PT, NVIDIA is hosting a Webinar explaining just what it looks like to run GPUs inside your Kubernetes cluster. Below is a further description of the event. You can register here.
Building AI powered cloud native applications allows organizations to integrate and deploy innovative features faster, scale on-demand, and optimize operational cost. AI powered enterprise applications are one of the fastest growing workloads in the hybrid cloud as organizations develop and deploy in the cloud and scale it on-prem overtime in a consistent manner.
The NVIDIA NGC catalog offers GPU-optimized AI software including framework containers and models that allow data scientists and developers to build their AI solutions faster. Red Hat OpenShift is a leading enterprise Kubernetes platform for Hybrid Cloud with integrated DevOps capabilities, enabling organizations globally to fast track AI projects from pilot to production.
In this session you will learn to:
Leverage the NVIDIA NGC catalog of GPU-optimized containers and models to build AI applications
Take advantage of Red Hat OpenShift to automate and streamline the development, deployment, and management of intelligent apps that include AI models, also known as DevOps for MLOps
Build a conversational AI solution, using BERT model with NGC and OpenShift on a public cloud
Join us after the presentation for a live Q&A session.
This is a guest blog by Dr. Ronen Dar, CTO and co-founder of Run:AI. At each stage of the machine learning / deep learning (ML/DL) process, researchers are completing specific tasks, and those tasks ...
The new Multi-Instance GPU (MIG) feature lets GPUs based on the NVIDIA Ampere architecture run multiple GPU-accelerated CUDA applications in parallel in a fully isolated way. The compute units of the ...