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Intel’s Al Gara Presents: Technology Opportunities Like Never Before

Al Gara from gave this talk at the Intel HPC Developer Conference in Denver. “Technology visionaries architecting the future of HPC and AI will share the key challenges as well as Intel’s direction. The talk will cover the adaptation of AI into HPC workflows, along their perspective architectural developments, upcoming transitions and range of solutions, technology opportunities, and the driving forces behind them.”

How AI is Reshaping HPC

Karl Freund from Moor Insights gave this talk at SC17. “Researchers have begun putting Machine Learning to work solving problems that do not lend themselves well to traditional numerical analysis, or that require unaffordable computational capacity. This talk with discuss three primary approaches being used today, and will share some case studies that show significant promise of lower latency, improved accuracy, and lower cost.”

Steve Oberlin from NVIDIA Presents: HPC Exascale & AI

Steve Oberlin from NVIDIA gave this talk at SC17 in Denver. “HPC is a fundamental pillar of modern science. From predicting weather to discovering drugs to finding new energy sources, researchers use large computing systems to simulate and predict our world. AI extends traditional HPC by letting researchers analyze massive amounts of data faster and more effectively. It’s a transformational new tool for gaining insights where simulation alone cannot fully predict the real world.”

Video: Red Hat Showcases ARM Support for HPC at SC17

In this video from SC17, Jon Masters from Red Hat describes the company’s Multi-Architecture HPC capabilities, including the new ARM-powered Apollo 70 server from HPE. “At SC17, you will also have an opportunity to see the power and flexibility of Red Hat Enterprise Linux across multiple architectures, including Arm v8-A, x86_64 and IBM POWER Little Endian.”

Adapting Deep Learning to New Data Using ORNL’s Titan Supercomputer

Travis Johnston from ORNL gave this talk at SC17. “Multi-node evolutionary neural networks for deep learning (MENNDL) is an evolutionary approach to performing this search. MENNDL is capable of evolving not only the numeric hyper-parameters, but is also capable of evolving the arrangement of layers within the network. The second approach is implemented using Apache Spark at scale on Titan. The technique we present is an improvement over hyper-parameter sweeps because we don’t require assumptions about independence of parameters and is more computationally feasible than grid-search.”

The AI Future is Closer than it Seems

Gadi Singer gave this talk at the Intel HPC Developer Conference in Denver. “Technology visionaries architecting the future of high-performance computing and artificial intelligence (AI) will share the key challenges as well as Intel’s direction. The talk will cover the adaptation of AI into HPC workflows, along their perspective architectural developments, upcoming transitions and range of solutions, technology opportunities, and the driving forces behind them.”

Visualization on GPU Accelerated Supercomputers

Peter Messmer from NVIDIA gave this talk at SC17. “This talk is a summary about the ongoing HPC visualization activities, as well as a description of the technologies behind the developer-zone shown in the booth.” Messmer is a principal software engineer in NVIDIA’s Developer Technology organization, working with clients to accelerate their scientific discovery process with GPUs.

Video: Deep Learning for Science

Prabhat from NERSC and Michael F. Wehner from LBNL gave this talk at the Intel HPC Developer Conference in Denver. “Deep Learning has revolutionized the fields of computer vision, speech recognition and control systems. Can Deep Learning (DL) work for scientific problems? This talk will explore a variety of Lawrence Berkeley National Laboratory’s applications that are currently benefiting from DL.”

Video: A Closer Look at the Atos Dibona Prototype for ARM-based HPC

In this video from SC17 in Denver, Pascale Bruner from Atos describes the company’s innovative ARM-HPC technologies developed as part of the Mont-Blanc Project. “Atos will showcase our Dibona prototype for ARM-based HPC. Named after the Dibona peak in the French Alps, the new prototype is part of the Phase 3 of Mont-Blanc and is based on 64 bit ThunderX2 processors from Cavium, relying on the ARM v8 instruction set.”

ESI Releases SimulationX 3.9 for Manufacturing

ESI Group has announced the release of SimulationX 3.9, a software platform for multiphysics system simulation. Designed for many industries – from automotive, energy, and mining to industrial machinery, railways, aerospace and aeronautics – SimulationX has proven to be one of the most reliable and customer-friendly solutions on the market.