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Penguin Computing Launches NVIDIA Tesla V100-based Servers

Today Penguin Computing announced strategic support for the field of artificial intelligence through availability of its servers based on the highly-advanced NVIDIA Tesla V100 GPU accelerator, powered by the NVIDIA Volta GPU architecture. “Deep learning, machine learning and artificial intelligence are vital tools for addressing the world’s most complex challenges and improving many aspects of our lives,” said William Wu, Director of Product Management, Penguin Computing. “Our breadth of products covers configurations that accelerate various demanding workloads – maximizing performance, minimizing P2P latency of multiple GPUs and providing minimal power consumption through creative cooling solutions.”

AMAX.AI Unveils [SMART]Rack Machine Learning Cluster

Today AMAX.AI launched the [SMART]Rack AI Machine Learning cluster, an all-inclusive rackscale platform is maximized for performance featuring up to 96x NVIDIA Tesla P40, P100 or V100 GPU cards, providing well over 1 PetaFLOP of compute power per rack. “The [SMART]Rack AI is revolutionary to Deep Learning data centers,” said Dr. Rene Meyer, VP of Technology, AMAX. “Because it not only provides the most powerful application-based computing power, but it expedites DL model training cycles by improving efficiency and manageability through integrated management, network, battery and cooling all in one enclosure.”

Server Vendors Announce NVIDIA Volta Systems for Accelerated AI

Today NVIDIA and its systems partners Dell EMC, Hewlett Packard Enterprise, IBM and Supermicro today unveiled more than 10 servers featuring NVIDIA Volta architecture-based Tesla V100 GPU accelerators — the world’s most advanced GPUs for AI and other compute-intensive workloads. “Volta systems built by our partners will ensure that enterprises around the world can access the technology they need to accelerate their AI research and deliver powerful new AI products and services,” said Ian Buck, vice president and general manager of Accelerated Computing at NVIDIA.

No speed limit on NVIDIA Volta with rise of AI

In this special guest feature, Brad McCredie from IBM writes that launch of Volta GPUs from NVIDIA heralds a new era of AI. “We’re excited about the launch of NVIDIA’s Volta GPU accelerators. Together with the NVIDIA NVLINK “information superhighway” at the core of our IBM Power Systems, it provides what we believe to be the closest thing to an unbounded platform for those working in machine learning and deep learning and those dealing with very large data sets.”

NVIDIA Brings Deep Learning to Hyperscale at GTC China

Today GTC China, NVIDIA made a series of announcements around Deep Learning, and GPU-accelerated computing for Hyperscale datacenters. “Demand is surging for technology that can accelerate the delivery of AI services of all kinds. And NVIDIA’s deep learning platform — which the company updated Tuesday with new inferencing software — promises to be the fastest, most efficient way to deliver these services.”

NVIDIA P100 GPUs come to Google Cloud Platform

Today the good folks at the Google Compute Platform announced the availability of NVIDIA GPUs in the Cloud for multiple geographies. Cloud GPUs can accelerate workloads such as machine learning training and inference, geophysical data processing, simulation, seismic analysis, molecular modeling, genomics and many more high performance compute use cases. “Today, we’re happy to make some massively parallel announcements for Cloud GPUs. First, Google Cloud Platform (GCP) gets another performance boost with the public launch of NVIDIA P100 GPUs in beta.

NASA Perspectives on Deep Learning

Nikunj Oza from NASA Ames gave this talk at the HPC User Forum. “This talk will give a broad overview of work at NASA in the space of data sciences, data mining, machine learning, and related areas at NASA. This will include work within the Data Sciences Group at NASA Ames, together with other groups at NASA and university and industry partners. We will delineate our thoughts on the roles of NASA, academia, and industry in advancing machine learning to help with NASA problems.”

JAIST in Japan installs Cray XC40 Supercomputer

Today Cray announced the Japan Advanced Institute for Science and Technology (JAIST) has put a Cray XC40 supercomputer into production. The Cray XC40 supercomputers incorporate the Aries high performance network interconnect for low latency and scalable global bandwidth, as well as the latest Intel Xeon processors, Intel Xeon Phi processors, and NVIDIA Tesla GPU accelerators. “Our new Cray XC40 supercomputer will support our mission of becoming a premier center of excellence in education and research.”

GPUs Accelerate Population Distribution Mapping Around the Globe

With the Earth’s population at 7 billion and growing, understanding population distribution is essential to meeting societal needs for infrastructure, resources and vital services. This article highlights how NVIDIA GPU-powered AI is accelerating mapping and analysis of population distribution around the globe. “If there is a disaster anywhere in the world,” said Bhaduri, “as soon as we have imaging we can create very useful information for responders, empowering recovery in a matter of hours rather than days.”

Machine & Deep Learning: Practical Deployments and Best Practices for the Next Two Years

Arno Kolster from Providentia Worldwide gave this talk at the HPC User Forum in Milwaukee. “Providentia Worldwide is a new venture in technology and solutions consulting which bridges the gap between High Performance Computing and Enterprise Hyperscale computing. We take the best practices from the most demanding compute environments in the world and apply those techniques and design patterns to your business.”