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Radio Free HPC Looks at Azure’s Move to GPUs and OCP for Deep Learning

In this podcast, the Radio Free HPC team looks at a set of IT and Science stories. Microsoft Azure is making a big move to GPUs and the OCP Platform as part of their Project Olympus. Meanwhile, Huawei is gaining market share in the server market and IBM is bringing storage to the atomic level.

E4 Computer Engineering’s Showcases New Petascale OCP Platform

Today E4 Computer Engineering from Italy showcased a new PetaFlops-Class Open Compute Server with “remarkable energy efficiency” based on the IBM POWER architecture. “Finding new ways of making easily deployable and energy efficient HPC solutions is often a complex task, which requires a lot of planning, testing and benchmarking – said Cosimo Gianfreda CTO, Co-Founder, E4 Computer Engineering. – We are very lucky to work with great partners like Wistron, as their timing and accuracy means we have all the right conditions to have effective time-to-market. I strongly believe that the performance on the node, coupled with the power monitoring technology, will receive a wide acceptance from the HPC and Enterprise community.”

Introduction to GPUs in HPC

“This video is from the opening session of the “Introduction to Programming Pascal (P100) with CUDA 8″ workshop at CSCS in Lugano, Switzerland. The three-day course is intended to offer an introduction to Pascal computing using CUDA 8.”

Nvidia Brings AI to the Cloud with the HGX-1 Hyperscale GPU Accelerator

Today, Microsoft, NVIDIA, and Ingrasys announced a new industry standard design to accelerate Artificial Intelligence in the next generation cloud. “Powered by eight NVIDIA Tesla P100 GPUs in each chassis, HGX-1 features an innovative switching design based on NVIDIA NVLink interconnect technology and the PCIe standard, enabling a CPU to dynamically connect to any number of GPUs. This allows cloud service providers that standardize on the HGX-1 infrastructure to offer customers a range of CPU and GPU machine instance configurations.”

NVIDIA Pascal GPUs come to Advanced Clustering Technologies

Missouri-based Advanced Clustering Technologies is helping customers solve challenges by integrating NVIDIA Tesla P100 accelerators into its line of high performance computing clusters. Advanced Clustering Technologies builds custom, turn-key HPC clusters that are used for a wide range of workloads including analytics, deep learning, life sciences, engineering simulation and modeling, climate and weather study, energy exploration, and improving manufacturing processes. “NVIDIA-enabled GPU clusters are proving very effective for our customers in academia, research and industry,” said Jim Paugh, Director of Sales at Advanced Clustering. “The Tesla P100 is a giant step forward in accelerating scientific research, which leads to breakthroughs in a wide variety of disciplines.”

Radio Free HPC Reviews the SC16 Student Cluster Competition Configurations & Results

In this podcast, the Radio Free HPC team reviews the results from SC16 Student Cluster Competition. “This year, the advent of clusters with the new Nvidia Tesla P100 GPUs made a huge impact, nearly tripling the Linpack record for the competition. For the first-time ever, the team that won top honors also won the award for achieving highest performance for the Linpack benchmark application. The team “SwanGeese” is from the University of Science and Technology of China. In traditional Chinese culture, the rare Swan Goose stands for teamwork, perseverance and bravery.”

NVIDIA Tesla P100 GPU Review

Accelerated computing continues to gain momentum as the HPC community moves towards Exascale. Our recent Tesla P100 GPU review shows how these accelerators are opening up new worlds of performance vs. traditional CPU-based systems and even vs. NVIDIA’s previous K80 GPU product. We’ve got benchmarks, case studies, and more in the insideHPC Research Report on GPU Accelerators.

Video: One Stop Systems Takes GPU Density to the Next Level at SC16

In this video from SC16, Nate Parada from One Stop Systems describes the company’s new High Density Compute Accelerator (HDCA) for Deep Learning. “The CA16000 High Density Compute Accelerator with sixteen NVIDIA Tesla GPU accelerators is used for a variety of HPC applications including oil and gas exploration and financial services. Completely integrated with the GPUs most suited for a specific application, it’s easy installation and tested reliability makes it superior to alternative products.”

New Cray XC50 Delivers 1 Petaflop Per Cabinet

Today Cray announced the launch of the Cray XC50 supercomputer – the company’s fastest supercomputer ever with a peak performance of one petaflop in a single cabinet. “Supercomputing applications are evolving to include more deep learning algorithms, and with this evolution, the uses for GPUs in our systems are increasing, enabling our customers to use new analytics techniques to gain insight from increasingly large and complex data,” said Ryan Waite, Cray senior vice president of products. “The new Cray XC50 system represents a major advancement in our supercomputing capabilities. It provides the highest performance density of any Cray supercomputer, and gives customers the computational resources they need to take on larger, more complex workloads, as well as the next generation of scientific challenges.”

CSIRO Deploys NVIDIA DGX-1 Deep Learning Supercomputers Down Under

Today NVIDIA announced APAC’s first deployment of NVIDIA DGX-1 deep learning supercomputers CSIRO in Australia. “There is a growing interest from research groups to adopt machine learning techniques to support their projects,” said Angus Macoustra, executive manager for Scientific Computing at CSIRO. “CSIRO research projects are already using the DGX-1 systems, and in time, it is expected that machine learning will have applicability across all our areas of research and be used by hundreds of researchers.”