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Record Number of Student Teams to Participate in the APAC HPC and AI Competition

The HPC-AI Advisory Council (HPCAIAC) in collaboration with the National Supercomputing Centre (NSCC) Singapore today announced the teams competing in the co-organized, third annual APAC HPC-AI Competition supporting student development and mastery in high performance computing and AI disciplines. Comprised of undergraduate and graduate competitors from some of Asia Pacific’s leading academic institutions, 30 teams […]

A2I POWER Processor Core Contributed to OpenPOWER Community

The IBM-led OpenPOWER Foundation announced the contribution of the IBM A2I POWER processor core design and associated FPGA environment to the open source ecosystem. The release, which took place today at the Linux Foundation Open Source Summit, follows the opening of the POWER Instruction Set Architecture (ISA) last August and is intended to enable the […]

SC20 General Chair: We’re Planning for In-Person and Virtual Conference

SC20, scheduled for November 15-20 in Atlanta, is in the throes of planning for this year’s conference amidst the global COVID-19 pandemic – and conference General Chair Christine E. Cuicchi today said that in the months since the coronavirus outbreak, “the SC20 committee began planning for both in-person and virtual attendance.” Noting that  open registration for the conference will begin on August 14, Cuicchi also said the conference planning committee will provide updates (here) on the event’s status as the course of the pandemic unfolds.

Video: Evolving Cyberinfrastructure, Democratizing Data, and Scaling AI to Catalyze Research Breakthroughs

Nick Nystrom from the Pittsburgh Supercomputing Center gave this talk at the Stanford HPC Conference. “The Artificial Intelligence and Big Data group at Pittsburgh Supercomputing Center converges Artificial Intelligence and high performance computing capabilities, empowering research to grow beyond prevailing constraints. The Bridges supercomputer is a uniquely capable resource for empowering research by bringing together HPC, AI and Big Data.”

Video: Machine Learning for Weather Forecasts

Peter Dueben from ECMWF gave this talk at the Stanford HPC Conference. “I will present recent studies that use deep learning to learn the equations of motion of the atmosphere, to emulate model components of weather forecast models and to enhance usability of weather forecasts. I will than talk about the main challenges for the application of deep learning in cutting-edge weather forecasts and suggest approaches to improve usability in the future.”

Agenda Posted for OpenFabrics Virtual Workshop

The OpenFabrics Alliance (OFA) has opened registration for its OFA Virtual Workshop, taking place June 8-12, 2020. This virtual event will provide fabric developers and users an opportunity to discuss emerging fabric technologies, collaborate on future industry requirements, and address today’s challenges. “The OpenFabrics Alliance is committed to accelerating the development of high performance fabrics. This virtual event will provide fabric developers and users an opportunity to discuss emerging fabric technologies, collaborate on future industry requirements, and address challenges.”

A Data-Centric Approach to Extreme-Scale Ab initio Dissipative Quantum Transport Simulations

Alexandros Ziogas from ETH Zurich gave this talk at Supercomputing Frontiers Europe. “The computational efficiency of a state of the art ab initio #quantum transport (QT) solver, capable of revealing the coupled electro-thermal properties of atomically-resolved nano-transistors, has been improved by up to two orders of magnitude through a data centric reorganization of the application. The approach yields coarse-and fine-grained data-movement characteristics that can be used for performance and communication modeling, communication-avoidance, and dataflow transformations.”

The Incorporation of Machine Learning into Scientific Simulations at LLNL

Katie Lewis from Lawrence Livermore National Laboratory gave this talk at the Stanford HPC Conference. “Today, data science, including machine learning, is one of the fastest growing areas of computing, and LLNL is investing in hardware, applications, and algorithms in this space. While the use of simulations to focus and understand experiments is well accepted in our community, machine learning brings new challenges that need to be addressed. I will explore applications for machine learning in scientific simulations that are showing promising results and further investigation that is needed to better understand its usefulness.”

Shaheen II Supercomputer to power COVID-19 research

KAUST has opened a call for proposals for COVID-19 research to be run on the Shaheen II supercomputer and related resources. Shaheen II joins many supercomputers around the world that have recently reallocated a portion of their resources to campaigns to model the pandemic. “In related news, “COVID-19 and High Performance Computing” is the subject of a special session of the now virtualized ISC 2020 conference, according to Professor David Keyes, Director of KAUST’s Extreme Computing Research Center, who is the Program Chair of the event.”

How to Achieve High-Performance, Scalable and Distributed DNN Training on Modern HPC Systems

DK Panda from Ohio State University gave this talk at the Stanford HPC Conference. “This talk will focus on a range of solutions being carried out in my group to address these challenges. The solutions will include: 1) MPI-driven Deep Learning, 2) Co-designing Deep Learning Stacks with High-Performance MPI, 3) Out-of- core DNN training, and 4) Hybrid (Data and Model) parallelism. Case studies to accelerate DNN training with popular frameworks like TensorFlow, PyTorch, MXNet and Caffe on modern HPC systems will be presented.”