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Video: Liqid Teams with Inspur at GTC for Composable Infrastructure

In this video from GTC 2018, Dolly Wu from Inspur and Marius Tudor from Liquid describe how the two companies are collaborating on Composable Infrastructure for AI and Deep Learning workloads. “AI and deep learning applications will determine the direction of next-generation infrastructure design, and we believe dynamically composing GPUs will be central to these emerging platforms,” said Dolly Wu, GM and VP Inspur Systems.

Why the World’s Largest Telescope Relies on GPUs

Over at the NVIDIA blog, Jamie Beckett writes that the new European-Extremely Large Telescope, or E-ELT, will capture images 15 times sharper than the dazzling shots the Hubble telescope has beamed to Earth for the past three decades. “are running GPU-powered simulations to predict how different configurations of E-ELT will affect image quality. Changes to the angle of the telescope’s mirrors, different numbers of cameras and other factors could improve image quality.”

DDN feeds NVIDIA DGX Servers 33GB/s for Machine Learning

Today DDN announced that its EXAScaler DGX solution accelerated client has been fully integrated with the NVIDIA DGX Architecture. “By supplying this groundbreaking level of performance, DDN enables customers to greatly accelerate their Machine Learning initiatives, reducing load wait times of large datasets to mere seconds for faster training turnaround.”

Video: VMware powers HPC Virtualization at NVIDIA GPU Technology Conference

In this video from from 2018 GPU Technology Conference, Ziv Kalmanovich from VMware and Fred Devoir from NVIDIA describe how they are working together to bring the benefits of virtualization to GPU workloads. “For cloud environments based on vSphere, you can deploy a machine learning workload yourself using GPUs via the VMware DirectPath I/O or vGPU technology.”

Liqid and Inspur team up for Composable GPU-Centric Rack-Scale Solutions

Today Liqid and Inspur announced that the two companies will offer a joint solution designed specifically for advanced, GPU-intensive applications and workflows. “Our goal is to work with the industry’s most innovative companies to build an adaptive data center infrastructure for the advancement of AI, scientific discovery, and next-generation GPU-centric workloads,” said Sumit Puri, CEO of Liqid. “Liqid is honored to be partnering with data center leaders Inspur Systems and NVIDIA to deliver the most advanced composable GPU platform on the market with Liqid’s fabric technology.”

Liqid Showcases Composable Infrastructure for GPUs at GTC 2017

“The Liqid Composable Infrastructure (CI) Platform is the first solution to support GPUs as a dynamic, assignable, bare-metal resource. With the addition of graphics processing, the Liqid CI Platform delivers the industry’s most fully realized approach to composable infrastructure architecture. With this technology, disaggregated pools of compute, networking, data storage and graphics processing elements can be deployed on demand as bare-metal resources and instantly repurposed when infrastructure needs change.”

Podcast: Marc Hamilton on how Volta GPUs will Power Next-Generation HPC and AI

In this podcast, Marc Hamilton from Nvidia describes how the new Volta GPUs will power the next generation of systems for HPC and AI. According to Nvidia, the Tesla V100 accelerator is the world’s highest performing parallel processor, designed to power the most computationally intensive HPC, AI, and graphics workloads.

Penguin Computing Adds Pascal GPUs to Open Compute Tundra Systems

“Pairing Tundra Relion X1904GT with our Tundra Relion 1930g, we now have a complete deep learning solution in Open Compute form factor that covers both training and inference requirements,” said William Wu, Director of Product Management at Penguin Computing. “With the ever evolving deep learning market, the X1904GT with its flexible PCI-E topologies eclipses the cookie cutter approach, providing a solution optimized for customers’ respective applications. Our collaboration with NVIDIA is combating the perennial need to overcome scaling challenges for deep learning and HPC.”

AI & Robotics Front and Center at GTC Japan

Robotics and Deep Learning applications were front and center at GTC Japan this week, where 2600 attendees lined up to hear the latest on GPU technologies. The age of AI is here,” said Jen-Hsun Huang, founder and CEO of NVIDIA. “‎GPU deep learning ignited this new wave of computing where software learns and machines reason. […]

Video: The Deep Learning AI Revolution

In this video from GTC 2016 in Taiwan, Nvidia CEO Jen-Hsun Huang unveils technology that will accelerate the deep learning revolution that is sweeping across industries. “AI computing will let us create machines that can learn and behave as humans do. It’s the reason why we believe this is the beginning of the age of AI.”