
Registration in FREE. For more information, see the Nvidia Site https://www.nvidia.com/gtc/

Registration in FREE. For more information, see the Nvidia Site https://www.nvidia.com/gtc/
A revisit on Nvidia GTC 2021. A worthwhile thought to think through.
NVIDIA BlueField-3 DPU, the most powerful software-defined, hardware-accelerated data center on a chip. The #datacenter is the new unit of computing and the BlueField-2 DPU is now available to offload and accelerate the networking, storage, and security tasks within overtaxed data centers.
NVIDIA and SIGGRAPH share a long history of innovation and discovery. Over the last 25 years our community has seen giant leaps forward, driven by brilliant minds and curious explorers. We are now upon the opening moments of an AI-powered revolution in computer graphics with massive advancements in rendering, AI, simulation, and compute technologies across every industry. With open standards and connected ecosystems, we are on the cusp of achieving a new way to interact and exist with graphics in shared virtual worlds.
In a special address at MWC Barcelona 2021, NVIDIA announced its partnership with Google Cloud to create the industry’s first AI-on-5G open innovation lab that will speed AI application development for 5G network operators.
Additional announcements included: ● Extending the 5G ecosystem with Arm CPU cores on NVIDIA BlueField-3 DPUs ● Launching NVIDIA CloudXR 3.0 with bidirectional audio for remote collaboration
Speaker: Marc Hamilton, VP of Solutions Architecture and Engineering, NVIDIA Panelists: Nicola Rieke, Dion Harris, Timothy Costa, Gilad Shainer, Geetika Gupta
Published twice a year and publicly available at www.top500.org, the TOP500 supercomputing list ranks the world’s most powerful computer systems according to the Linpack benchmark rating system.

Summary of Findings for Nvidia Networking.
by NVIDIA CEO Jensen Huang’s Teratec Keynote: The Industrial HPC Revolution
The Transformational Power of Accelerated Computing, From Gaming to the Enterprise Data Center.

This is an interesting write-up from James Mauro from Nvidia on Storage Performance Basics for Deep Learning.
“The complexity of the workloads plus the volume of data required to feed deep-learning training creates a challenging performance environment. Deep learning workloads cut across a broad array of data sources (images, binary data, etc), imposing different disk IO load attributes, depending on the model and a myriad of parameters and variables.”
For Further Reads… Do take a look at https://developer.nvidia.com/blog/storage-performance-basics-for-deep-learning/
The NGC catalog is a hub of GPU-optimized AI, high-performance computing (HPC), and data analytics software that simplifies and accelerates end-to-end workflows