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AMD Powers Corona Cluster for HPC Analytics at Livermore

Lawrence Livermore National Lab has deployed a 170-node HPC cluster from Penguin Computing. Based on AMD EPYC processors and Radeon Instinct GPUs, the new Corona cluster will be used to support the NNSA Advanced Simulation and Computing (ASC) program in an unclassified site dedicated to partnerships with American industry. “Even as we do more of our computing on GPUs, many of our codes have serial aspects that need really good single core performance. That lines up well with AMD EPYC.”

Scaling Deep Learning for Scientific Workloads on the #1 Summit Supercomputer

Jack Wells from ORNL gave this talk at the GPU Technology Conference. “HPC centers have been traditionally configured for simulation workloads, but deep learning has been increasingly applied alongside simulation on scientific datasets. These frameworks do not always fit well with job schedulers, large parallel file systems, and MPI backends. We’ll share benchmarks between native compiled versus containers on Power systems, like Summit, as well as best practices for deploying learning and models on HPC resources on scientific workflows.”

Video: NVIDIA Showcases Programmable Acceleration of multiple Domains with one Architecture

In this video from GTC 2019 in Silicon Valley, Marc Hamilton from NVIDIA describes how accelerated computing is powering AI, computer graphics, data science, robotics, automotive, and more. “Well, we always make so many great announcements at GTC. But one of the traditions Jensen has now started a few years ago is coming up with a new acronym to really make our messaging for the show very, very simple to remember. So PRADA stands for Programmable Acceleration Multiple Domains One Architecture. And that’s really what the GPU has become.”

How Mellanox SHARP technology speeds Ai workloads

Mellanox Scalable Hierarchical Aggregation and Reduction Protocol (SHARP) technology improves upon the performance of MPI operations by offloading collective operations from the CPU to the switch network, and by eliminating the need to send data multiple times between endpoints. This innovative approach decreases the amount of data traversing the network as aggregation nodes are reached, and dramatically reduces the MPI operations time. Implementing collective communication algorithms in the network also has additional benefits, such as freeing up valuable CPU resources for computation rather than using them to process communication.”

Video: Jensen Huang Keynote and News Recap from GPU Technology Conference

In this video, NVIDIA CEO Jensen Huang delivers a sweeping opening keynote at San Jose State University, describing the company’s progress accelerating the sprawling datacenters that power the world’s most dynamic industries. “As a highlight, Mellanox CEO Eyal Waldman joined Huang on stage to describe how the two company’s technologies power more than half the world’s TOP500 fastest supercomputers.”

Mellanox HDR 200G InfiniBand Speeds Machine Learning with NVIDIA

Today Mellanox announced that its HDR 200G InfiniBand with the “Scalable Hierarchical Aggregation and Reduction Protocol” (SHARP) technology has set new performance records, doubling deep learning operations performance. The combination of Mellanox In-Network Computing SHARP with NVIDIA 100 Tensor Core GPU technology and Collective Communications Library (NCCL) deliver leading efficiency and scalability to deep learning and artificial intelligence applications.

Swiss HPC Conference to Focus on Intersecting Interests, Industries, and Initiatives

Coming up in April, AI and HPC practitioners share passions for cutting-edge technology and breakthrough R&D in Lugano, Switzerland at the tenth annual Swiss Conference and HPCXXL User Group. The joint sessions take place at Palazzo dei Congressi, April 1-4, bringing leaders together from academia, government and industry to share first-hand insights on innovative research, techniques, tools and technologies that are fueling economies, productivity and progress globally.

Mellanox NVMe SNAP Technology to Simplify Composable Storage

Today Mellanox announced NVMe SNAP (Software-defined, Network Accelerated Processing), a storage virtualization solution for public cloud, private cloud and enterprise computing. This new SNAP technology allows customers to compose remote server-attached NVMe Flash storage and access it as if it were local, to achieve all the efficiency and management benefits of remote storage, with the simplicity of local storage.

Radio Free HPC Looks at NVIDIA’s acquisition of Mellanox

In this podcast, the Radio Free HPC team looks at NVIDIA’s acquisition of Mellanox. “This called for an emergency session of our crack panel. While it will be several months before the full impact of this merger is felt, the RFHPC team believes this will change both the HPC and the Datacenter markets. It also signals Nvidia’s journey towards becoming more of a systems company and gives them a better shot at the enterprise AI market.”

NVIDIA to Purchase Mellanox for $6.9 Billion

Today NVIDIA announced plans to acquire Mellanox for approximately $6.9 billion. The acquisition will unite two of the world’s leading companies in HPC. Together, NVIDIA’s computing platform and Mellanox’s interconnects power over 250 of the world’s TOP500 supercomputers and have as customers every major cloud service provider and computer maker.