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ISC 2017 Distinguished Talks to Focus on Data Analytics in Manufacturing & Science

Today ISC 2017 announced that it’s Distinguished Talk series will focus on Data Analytics in manufacturing and scientific applications. One of the Distinguished Talks will be given by Dr. Sabine Jeschke from the Cybernetics Lab at the RWTH Aachen University on the topic of, “Robots in Crowds – Robots and Clouds.” Jeschke’s presentation will be followed by one from physicist Kerstin Tackmann, from the German Electron Synchrotron (DESY) research center, who will discuss big data and machine learning techniques used for the ATLAS experiment at the Large Hadron Collider.

Defining AI, Machine Learning, and Deep Learning

“In this guide, we take a high-level view of AI and deep learning in terms of how it’s being used and what technological advances have made it possible. We also explain the difference between AI, machine learning and deep learning, and examine the intersection of AI and HPC. We also present the results of a recent insideBIGDATA survey to see how well these new technologies are being received. Finally, we take a look at a number of high-profile use case examples showing the effective use of AI in a variety of problem domains.”

Podcast: Democratizing Education for the Next Wave of AI

“Coursera has named Intel as one of its first corporate content partners. Together, Coursera and Intel will develop and distribute courses to democratize access to artificial intelligence and machine learning. In this interview, Ibrahim talks about her and Coursera’s history, reports on Coursera’s progress delivering education at massive scale, and discusses Coursera and Intel’s unique partnership for AI.”

Video: Computing of the Future

Jeffrey Welser from IBM Research Almaden presented this talk at the Stanford HPC Conference. “Whether exploring new technical capabilities, collaborating on ethical practices or applying Watson technology to cancer research, financial decision-making, oil exploration or educational toys, IBM Research is shaping the future of AI.”

Job of the Week: Senior HPC Systems Administrator at Purdue

Purdue University is seeking a Senior HPC Systems Administrator in our Job of the Week. “In this role, you will assist world renowned researchers in advancing science. Additionally, as Senior HPC Systems Administrator, you will be responsible for large sections of Purdue’s innovative computational research environment and help set direction of future research systems. This role requires an individual to work closely with researchers, systems administrators, and developers throughout the University and partner institutions to develop large-impact projects and computational systems.”

Huawei: A Fresh Look at High Performance Computing

Francis Lam from Huawei presented this talk at the Stanford HPC Conference. “High performance computing is rapidly finding new uses in many applications and businesses, enabling the creation of disruptive products and services. Huawei, a global leader in information and communication technologies, brings a broad spectrum of innovative solutions to HPC. This talk examines Huawei’s world class HPC solutions and explores creative new ways to solve HPC problems.

Supercomputing Transportation System Data using TACC’s Rustler

Over at TACC, Faith Singer-Villalobos writes that researchers are using the Rustler supercomputer to tackle Big Data from self-driving connected vehicles (CVs). “The volume and complexity of CV data are tremendous and present a big data challenge for the transportation research community,” said Natalia Ruiz-Juri, a research associate with The University of Texas at Austin’s Center for Transportation Research. While there is uncertainty in the characteristics of the data that will eventually be available, the ability to efficiently explore existing datasets is paramount.

ORNL’s Al Geist to Keynote OpenFabrics Workshop in Austin

In his keynote, Mr. Geist will discuss the need for future Department of Energy supercomputers to solve emerging data science and machine learning problems in addition to running traditional modeling and simulation applications. In August 2016, the Exascale Computing Project (ECP) was approved to support a huge lift in the trajectory of U.S. High Performance Computing (HPC). The ECP goals are intended to enable the delivery of capable exascale computers in 2022 and one early exascale system in 2021, which will foster a rich exascale ecosystem and work toward ensuring continued U.S. leadership in HPC. He will also share how the ECP plans to achieve these goals and the potential positive impacts for OFA.

Designing HPC & Deep Learning Middleware for Exascale Systems

DK Panda from Ohio State University presented this deck at the 2017 HPC Advisory Council Stanford Conference. “This talk will focus on challenges in designing runtime environments for exascale systems with millions of processors and accelerators to support various programming models. We will focus on MPI, PGAS (OpenSHMEM, CAF, UPC and UPC++) and Hybrid MPI+PGAS programming models by taking into account support for multi-core, high-performance networks, accelerators (GPGPUs and Intel MIC), virtualization technologies (KVM, Docker, and Singularity), and energy-awareness. Features and sample performance numbers from the MVAPICH2 libraries will be presented.”

Radio Free HPC Looks at the Posit and Next Generation Computer Arithmetic

In this podcast, the Radio Free HPC team discusses a recent presentation by John Gustafson on Next Generation Computer Arithmetic. “A new data type called a “posit” is designed for direct drop-in replacement for IEEE Standard 754 floats. Unlike unum arithmetic, posits do not require interval-type mathematics or variable size operands, and they round if an answer is inexact, much the way floats do. However, they provide compelling advantages over floats, including simpler hardware implementation that scales from as few as two-bit operands to thousands of bits.”