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Microway GPU Systems for HPC & Deep Learning at GTC 2017

In this video from the 2017 GPU Technology Conference, Eliot Eshelman from Microway describes the company’s GPU expertise and wide range of accelerated HPC products. “Since 1982, Microway has delivered high performance computing solutions. We have in-depth experience with demanding Linux-based scientific/engineering applications. Leveraging NVIDIA’s latest Tesla GPUs, our team will design a solution for your specific applications. Our experts ensure your system is delivered fully tested and ready to run!”

Video: Computational Fluid Dynamics for Surgical Planning

“The current versions of the codes use MPI and depend on finer and finer meshes for higher accuracy which are computationally demanding. To overcome the demands, the team has gained access to their state-of-the-art cluster equipped with POWER CPUs and Tesla P100 GPUs — and turning to OpenACC and machine learning to accelerate their science. This has allowed them to spend the least resources on programming, and effectively utilize available compute resources.”

Overview of the HGX-1 AI Accelerator Chassis

“The Project Olympus hyperscale GPU accelerator chassis for AI, also referred to as HGX-1, is designed to support eight of the latest “Pascal” generation NVIDIA GPUs and NVIDIA’s NVLink high speed multi-GPU interconnect technology, and provides high bandwidth interconnectivity for up to 32 GPUs by connecting four HGX-1 together. The HGX-1 AI accelerator provides extreme performance scalability to meet the demanding requirements of fast growing machine learning workloads, and its unique design allows it to be easily adopted into existing datacenters around the world.”

Nvidia to Power Fujitsu’s New Deep Learning System at RIKEN

Today Fujitsu announced that it has received RIKEN’s order for the “Deep learning system,” one of the largest supercomputers in Japan specializing in AI research. “NVIDIA DGX-1, the world’s first all-in-one AI supercomputer, is designed to meet the enormous computational needs of AI researchers,” said Jim McHugh, VP & GM at Nvidia. “Powered by 24 DGX-1s, the RIKEN Center for Advanced Intelligence Project’s system will be the most powerful DGX-1 customer installation in the world. Its breakthrough performance will dramatically speed up deep learning research in Japan, and become a platform for solving complex problems in healthcare, manufacturing and public safety.”

Apply Now for Summer of HPC 2017 in Barcelona

“The PRACE Summer of HPC is an outreach and training program that offers summer placements at top High Performance Computing centers across Europe to late-stage undergraduates and early-stage postgraduate students. Up to twenty top applicants from across Europe will be selected to participate. Participants will spend two months working on projects related to PRACE technical or industrial work and produce a report and a visualization or video of their results.”

Supermicro Showcases Versatile HPC Solutions at SC16

In this video from SC16, Don Clegg from Supermicro describes the company’s broad range of HPC solutions. “Innovation is at the core of Supermicro product development and benefits the HPC community with first-to-market integration of advanced technology such as our 1U with four and 4U with eight Pascal P100 SXM2 GPUs or 4U with ten PCI-e GPU systems, hot-swap U.2 NVMe, upcoming fabric technologies like Red Rock Canyon and PCI-E switches, as well as new architecture designs like our new high-density BigTwin system design.”

GPUs & Deep Learning in the Spotlight for Nvidia at SC16

In this video from SC16, Roy Kim from Nvidia describes how the company is bringing in a new age of AI with accelerated computing for Deep Learning applications. “Deep learning is the fastest-growing field in artificial intelligence, helping computers make sense of infinite amounts of data in the form of images, sound, and text. Using multiple levels of neural networks, computers now have the capacity to see, learn, and react to complex situations as well or better than humans. This is leading to a profoundly different way of thinking about your data, your technology, and the products and services you deliver.”

HPE Apollo 6500 for Deep Learning

“With up to eight high performance NVIDIA GPUs designed for maximum transfer bandwidth, the HPE Apollo 6500 is purpose-built for HPC and deep learning applications. Its high ratio of GPUs to CPUs, dense 4U form factor and efficient design enable organizations to run deep learning recommendation algorithms faster and more efficiently, significantly reducing model training time and accelerating the delivery of real-time results, all while controlling costs.”

NVLink Speeds Deep Learning on New OpenPOWER Servers

Over at the IBM System Blog, Sumit Gupta writes that the company’s new IBM Power System 822LC with Nvidia Tesla P100 GPUs is already demonstrating impressive performance on Deep Learning training applications. “A single S822LC for HPC with four NVIDIA Tesla P100 GPUs is 2.2 times faster reaching 50 percent accuracy in AlexNet than a server with four NVIDIA Tesla M40 GPUs!”

Power8 Systems with NVLink Come to Nimbix HPC Cloud

Today’s emerging workloads like machine and deep learning, artificial intelligence, accelerated databases, and high performance data analytics require incredible speed through accelerated computing,” said Sumit Gupta, Vice President, High Performance Computing and Data Analytics, IBM. “Delivering the capabilities of the new IBM POWER8 with NVIDIA NVLink-based system through the Nimbix cloud expands the horizons of HPC and brings a highly differentiated accelerated computing platform to a whole new set of users.”