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AMD: Delivering the Future of High-Performance Computing

Dr. Lisa Su from AMD gave this talk at the recent DARPA Electronics Resurgence Initiative Summit. “Optimum system performance requires co-design of silicon chips, system architecture, and software. She presented the example of the Frontier exascale computer system being developed for Oak Ridge National Lab, which should exhibit 1.5 exaflops by 2021. While the highest-performance chips and systems will initially be limited to the most expensive machines, it is expected that similar technology will become available within a few years in data centers, edge computers, and even mobile devices.”

The ABCI Supercomputer: World’s First Open AI Computing Infrastructure

Shinichiro Takizawa from AIST gave this talk at the MVAPICH User Group. “ABCI is the world’s first large-scale Open AI Computing Infrastructure, constructed and operated by AIST, Japan. It delivers 19.9 petaflops of HPL performance and world’ fastest training time of 1.17 minutes in ResNet-50 training on ImageNet datasets as of July 2019. In this talk, we focus on ABCI’s network architecture and communication libraries available on ABCI and shows their performance and recent research achievements.”

NVIDIA Powers GRC Immersion Cooled System at TACC

Today GRC announced its joint project with NVIDIA to help power a GPU-intensive computing subsystem for TACC’s Frontera Supercomputer, the world’s largest academic supercomputer. GRC is proud of its long history with TACC and we’re delighted to have been able to collaborate once again with NVIDIA to help power the next generation of academic research,” […]

NVIDIA to Accelerate Machine Learning on VMware Cloud

Today NVIDIA and VMware announced plans to deliver accelerated GPU services for VMware Cloud on AWS to power modern enterprise applications, including AI, machine learning and data analytics workflows. These services will enable customers to seamlessly migrate VMware vSphere-based applications and containers to the cloud, unchanged, where they can be modernized to take advantage of high-performance computing, machine learning, data analytics and video processing applications.

Mellanox Powers Virtualized Machine Learning with VMware and NVIDIA

Today Mellanox announced that its RDMA (Remote Direct Memory Access) networking solutions for VMware vSphere enable virtualized Machine Learning solutions that achieve higher GPU utilization and efficiency. “As Moore’s Law has slowed, traditional CPU and networking technologies are no longer sufficient to support the emerging machine learning workloads,” said Kevin Deierling, vice president marketing, Mellanox Technologies. “Using hardware compute accelerators such as NVIDIA T4 GPUs and Mellanox’s RDMA networking solutions has proven to boost application performance in virtualized deployments.”

IBM’s HPC Dreams are Tattered

In this special guest feature, Dan Olds from OrionX.net writes that IBM ambitions in the HPC market have fallen short. “Without more commitment and support, IBM’s POWER processor runs the risk of becoming this generations version of the DEC Alpha CPU. It was a fantastic processor and ran rings around competitors, but ultimately failed because of a lack of marketing and operating environment support from DEC.”

Video: Unboxing the NVIDIA DGX-1 Supercomputer at Georgia Tech

In this video, Oded Green from NVIDIA unboxes a DGX-1 supercomputer at the College of Computing Data Center at Georgia Tech. “And while the DGX-1 arriving at Georgia Tech for student-use is exciting enough, there is cause for more celebration as a DGX Station also arrived this year as part of a new NVIDIA Artificial Intelligence Lab (NVAIL) grant awarded to CSE. The NVAIL grant focuses on developing multi-GPU graph analytics and the DGX station is constructed specifically for data science and artificial intelligence development.”

Supercomputing Galactic Winds with Cholla

Using the Titan supercomputer at Oak Ridge National Laboratory, a team of astrophysicists created a set of galactic wind simulations of the highest resolution ever performed. The simulations will allow researchers to gather and interpret more accurate, detailed data that elucidates how galactic winds affect the formation and evolution of galaxies.

Volkov and Demmel Paper on GPUs Wins SC19 Test of Time Award

Today SC19 announced the winners of the Test of Time Award. The annual award recognizes an outstanding paper that has deeply influenced the HPC discipline. We are pleased to announce the selection of the SC08 paper, “Benchmarking GPUs to Tune Dense Linear Algebra”, by Vasily Volkov (NVIDIA) and James Demmel (UC Berkeley) as the SC19 ToTA winner.

The paper was deemed deserving of the SC19 ToTA due to its first-of-its-kind vision of GPU architectures as a vector machine. By building on this vision, Volkov and Demmel defined techniques to achieve greater efficiency and performance.

Video: NVIDIA Accelerates Conversational AI

In this video, NVIDIA’s Bryan Catanzaro explains how recent breakthroughs in natural language understanding bring us one step closer to conversational AI. “Today NVIDIA announced breakthroughs in language understanding that allow businesses to engage more naturally with customers using real-time conversational AI. “NVIDIA’s groundbreaking work accelerating these models allows organizations to create new, state-of-the-art services that can assist and delight their customers in ways never before imagined.”