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Addison Snell Presents: HPC Computing Trends

Addison Snell presented this deck at the Stanford HPC Conference. “Intersect360 Research returns with an annual deep dive into the trends, technologies and usage models that will be propelling the HPC community through 2017 and beyond. Emerging areas of focus and opportunities to expand will be explored along with insightful observations needed to support measurably positive decision making within your operations.”

Video: The Era of Self-Tuning Servers

“Servers today have hundreds of knobs that can be tuned for performance and energy efficiency. While some of these knobs can have a dramatic effect on these metrics, manually tuning them is a tedious task. It is very labor intensive, it requires a lot of expertise, and the tuned settings are only relevant for the hardware and software that were used in the tuning process. In addition to that, manual tuning can’t take advantage of application phases that may each require different settings. In this presentation, we will talk about the concept of dynamic tuning and its advantages. We will also demo how to improve performance using manual tuning as well as dynamic tuning using DatArcs Optimizer.”

Call for Panels: SC17 in Denver

SC17 has issued its Call for Panel Sessions. The conference takes place Nov. 12-17 in Denver. “As in past years, panels at SC17 will be some of the most heavily attended events of the Conference. Panels will bring together the key thinkers and producers in the field to consider in a lively and rapid-fire context some of the key questions challenging high performance computing, networking, storage and associated analysis technologies for the foreseeable future.”

Deep Learning & HPC: New Challenges for Large Scale Computing

“In recent years, major breakthroughs were achieved in different fields using deep learning. From image segmentation, speech recognition or self-driving cars, deep learning is everywhere. Performance of image classification, segmentation, localization have reached levels not seen before thanks to GPUs and large scale GPU-based deployments, leading deep learning to be a first class HPC workload.”

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.

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.”

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.

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.”

Call for Participation: PEARC17 in New Orleans

The PEARC17 Conference has issued its Call for Participation. Formerly known as the Extreme Science and Engineering Discovery Environment (XSEDE) annual conference, PEARC17 will take place July 9-13 in New Orleans. “The Technical Program for the PEARC17 includes four Paper tracks, Tutorials, Posters, a Visualization Showcase and Birds of a Feather (BoF) sessions. All submissions should emphasize experiences and lessons derived from operation and use of advanced research computing on campuses or provided for the academic and open science communities. Submissions aligned with the conference theme—Sustainability, Success, and Impact—are particularly encouraged.”