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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.”

Converging HPC, Big Data, and AI at the Tokyo Institute of Technology

Satoshi Matsuoka from the Tokyo Institute of Technology gave this talk at the NVIDIA booth at SC17. “TSUBAME3 embodies various BYTES-oriented features to allow for HPC to BD/AI convergence at scale, including significant scalable horizontal bandwidth as well as support for deep memory hierarchy and capacity, along with high flops in low precision arithmetic for deep learning.”

Intel Omni-Path Architecture: The Real Numbers

In this slidecast, Joe Yaworski from Intel describes the Intel Omni-Path architecture and how it scales performance for a wide range of HPC applications. He also shows why recently published benchmarks have not  reflected the real performance story.

Microsoft to acquire Avere Systems

Over at the Microsoft Blog, Jason Zander writes that the company is acquiring Avere Systems. “By bringing together Avere’s storage expertise with the power of Microsoft’s cloud, customers will benefit from industry-leading innovations that enable the largest, most complex high-performance workloads to run in Microsoft Azure. We are excited to welcome Avere to Microsoft, and look forward to the impact their technology and the team will have on Azure and the customer experience.”

Red Hat steps up with Multi-Architecture Solutions for HPC

In this video from SC17, Dan McGuan and Jon Masters from Red Hat describe the company’s Multi-Architecture HPC capabilities. “At SC17, you will 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.”

Dr. Pradeep Dubey on AI & The Virtuous Cycle of Compute

“Deep Learning was recently scaled to obtain 15PF performance on the Cori supercomputer at NERSC. Cori Phase II features over 9600 KNL processors. It can significantly impact how we do computing and what computing can do for us. In this podcast, I will discuss some of the application-level opportunities and system-level challenges that lie at the heart of this intersection of traditional high performance computing with emerging data-intensive computing.”

Video: Dell EMC AI Vision & Strategy

Jay Boisseau from Dell EMC gave this talk at SC17 in Denver. “Across every industry, organizations are moving aggressively to adopt AI | ML | DL tools and frameworks to help them become more effective in leveraging data and analytics to power their key business and operational use cases. To help our clients exploit the business and operational benefits of AI | ML | DL, Dell EMC has created “Ready Bundles” that are designed to simplify the configuration, deployment and management of AI | ML | DL solutions.”

Harp-DAAL: A Next Generation Platform for High Performance Machine Learning on HPC-Cloud

Judy Qiu from Indiana University gave this Invited Talk at SC17. “Our research has concentrated on runtime and data management to support HPC-ABDS. This is illustrated by our open source software Harp, a plug-in for native Apache Hadoop, which has a convenient science interface, high performance communication, and can invoke Intel’s Data Analytics Acceleration Library (DAAL). We are building a scalable parallel Machine Learning library that includes routines in Apache Mahout, MLlib, and others built in an NSF funded collaboration.”