Lee Bushen, NVIDIA Solutions Architect, gives you a walk-through of the installation process for NVIDIA Virtual GPU on VMware vSphere and Citrix Hypervisor (XenServer).
Nvidia
Deep Learning Flower Classification Inference on Nvidia A100
NVIDIA GauGAN Meets Jarvis: Create Photorealistic Images With Your Voice
The demo lets users instantly generate photorealistic landscapes using simple voice commands. The app is based on NVIDIA’s conversational AI framework called Jarvis with GauGAN.
Testing compatibility of Gromacs with CUDA Drivers
To test whether you have compiled your GROMACS correctly with the CUDA drivers and runtime. You can use the command
% gmx_mpi --version
You should see
GPU support: CUDA ..... ..... CUDA driver: 10.10 CUDA runtime: 10.10
Tensor Cores in a Nutshell
Build Your Own Conversational AI Application with NVIDIA Jarvis
Maximizing Performance for Distributed Machine Learning and Deep Learning with SHARP
The NVIDIA Mellanox Scalable Hierarchical Aggregation and Reduction Protocol (SHARP) takes advantage of the in-network computing capabilities in the NVIDIA Mellanox Quantum switch, dramatically improving the performance of distributed machine learning workloads.
Installing CUDA Python
How to install CUDA Python followed by a tutorial on how to run a Python example on a GPU
Digital Scalable multi-node training for AI jobs on NVIDIA DGX, OpenShift and Spectrum Scale
Nvidia and IBM did a complex proof-of-concept to demonstrate the scaling of AI workload using Nvidia DGX, Red Hat OpenShift and IBM Spectrum Scale at the example of ResNet-50 and the segmentation of images using the Audi A2D2 dataset. The project team published an IBM Redpaper with all the technical details and will present the key learnings and results.
The Linux Cluster 