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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.”

Why Rescale is one of the Fastest Growing Enterprise Software Companies of 2017

Over at the Rescale Blog, Joris Poort writes that the company has been named one of the fastest growing enterprise software companies of 2017. “It’s been a busy year as we’ve landed over 100 new enterprise customers, fueling our rapid growth in multiple key industry verticals including aerospace, automotive, life sciences, universities and with broad geographic coverage throughout the Americas, Europe, and Asia.”

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.”

Video: Deep Learning at 15 Petaflops

Narayanan Sundaram gave this talk at the Intel HPC Developer Conference. “We present the first 15-PetaFLOP Deep Learning system for solving supervised and semi-supervised scientific pattern classification problems, optimized for Intel Xeon Phi. We use a hybrid of synchronous and asynchronous training to scale to ~9600 nodes of Cori on CNN and autoencoder networks.”

Jack Dongarra Presents: Overview of HPC and Energy Savings on NVIDIA’s V100

Jack Dongarra from the University of Tennessee gave this talk at SC17. “In this talk we will look at the current state of high performance computing and look to the future toward exascale. In addition, we will examine some issues that can help in reducing the power consumption for linear algebra computations.”