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Stepping up Qubit research at the DOE

To use quantum computers on a large scale, we need to improve the technology at their heart – qubits. Qubits are the quantum version of conventional computers’ most basic form of information, bits. The DOE’s Office of Science is supporting research into developing the ingredients and recipes to build these challenging qubits.

Postdoc Symposium at Berkeley Lab Looks to Exascale for Modeling and Simulation

Twenty-two postdoctoral fellows from across the Computing Sciences Area shared the status of their current projects at the first CSA Postdoc Symposium, held January 30-31 at Berkeley Lab. Their presentations covered a broad range of research topics, including code optimization, machine/deep learning, network routing, modeling and simulation of complex scientific problems, exascale, and other next-generation computer architectures.

Podcast: Solving Multiphysics Problems at the Exascale Computing Project

In this Let’s Talk Exascale Podcast, Stuart Slattery and Damien Lebrun-Grandie from ORNL describe how they are readying algorithms for next-generation supercomputers at the Department of Energy. “The mathematical library development portfolio of the Software Technology (ST) research focus area of the ECP provides general tools to implement complex algorithms. These algorithms are designed to scale up for supercomputers so that ECP teams can then use them to accelerate the development and improve the performance of science applications on DOE high-performance computing architectures.”

Interview: Exascale Computing Project Update for 2020

In this video, Exascale Computing Project Director Doug Kothe describes how disciplined and tailored project management led to very impressive results in what was likely the most comprehensive independent review of the project to date. “ECP’s products will be robust, production ready, and functional right out of the box; and ECP is driving the sharing of information through regular training not only with ECP participants but also the broader US high-performance computing community to lower barriers to using exascale systems and accelerated architectures in general.”

Podcast: AMD to Power New ECMWF Supercomputer for Weather Forecasting

In this podcast, the Radio Free HPC looks at the new ECMWF supercomputer. “This new system will give them roughly 5x more compute power than their current system. The new box is an Atos BullSequana XH2000 fueled by high-end AMD 7742 Epyc processors, which will be the most powerful weather computer in the world. During the conversation we look at the history of ECMWF vendors, discuss the implications on weather forecasts given the power of this new system and the computational difficulties inherent in weather prediction.”

Arm HPC User Group to Host First Annual Meeting in Portugal

Arm’s HPC User Group (A-HUG) is transitioning to a fully-fledged community-led organization to better support the Arm ecosystem. The first annual meeting of the community-lead A-HUG will be held March 12-13 in Porto, Portugal. “The A-HUG event will include a hands-on training event and excellent talks covering the broad landscape of early systems & experience, near-term expectations for new hardware, and long term trends for architectures.”

Podcast: Rewriting NWChem for Exascale

In this Let’s Talk Exascale podcast, researchers from the NWChemEx project team describe how they are readying the popular code for Exascale. The NWChemEx team’s most significant success so far has been to scale coupled-cluster calculations to a much larger number of processors. “In NWChem we had the global arrays as a toolkit to be able to build parallel applications.”

DIII-D Researchers Use Machine Learning to Steer Fusion Plasmas

Researchers at the DIII-D National Fusion Facility achieved a scientific first this month when they used machine learning calculations to automatically prevent fusion plasma disruptions in real time, while simultaneously optimizing the plasma for peak performance. The new experiments are the first of what they expect to be a wave of research in which machine learning–augmented controls could broaden the understanding of fusion plasmas. The work may also help deliver reliable, peak performance operation of future fusion reactors.

Video: Data Parallel Deep Learning

Huihuo Zheng from Argonne National Laboratory gave this talk at ATPESC 2019. “The Argonne Training Program on Extreme-Scale Computing (ATPESC) provides intensive, two weeks of training on the key skills, approaches, and tools to design, implement, and execute computational science and engineering applications on current high-end computing systems and the leadership-class computing systems of the future.”

ECP Report: Advancing Scientific Productivity through Better Scientific Software

The Exascale Computing Project has published a new report to foster and advance software productivity and sustainability for extreme-scale computational science. The report introduces work by the IDEAS-ECP project, explaining its approach, outcomes, and impact of work in partnership with the ECP and broader computational science community. The DOE Exascale Computing Project (ECP) provides a […]