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Advances in the Fields of Atmospheric Science, Climate, and Weather

Susan Bates from NCAR gave this talk at the Blue Waters Summit. “For the past five years, the Blue Waters Project has provided an invaluable platform for research in the fields of atmospheric science, climate, and weather. The computationally intensive numerical models running on Blue Waters push the limits of model resolution and/or capability in first-of-their-kind simulations.”

Containers: Shifter and Singularity on Blue Waters

In this video from the Blue Waters 2018 Symposium, Maxim Belkin presents a tutorial on Containers: Shifter and Singularity on Blue Waters. “Container solutions are a great way to seamlessly execute code on a variety of platforms. Not only they are used to abstract away from the software stack of the underlying operating system, they also enable reproducible computational research. In this mini-tutorial, I will review the process of working with Shifter and Singularity on Blue Waters.”

Video: Massive Galaxies and Black Holes at the Cosmic Dawn

Tiziana DiMatteo from Carnegie Melon University gave this talk at the 2018 Blue Waters Symposium. “The first billion years is a pivotal time for cosmic structure formation. The galaxies and black holes that form then shape and influence all future generations of stars and black holes. Understanding and detecting the the first galaxies and black holes is therefore one of the main observational and theoretical challenges in galaxy formation.”

Machine Learning with Python: Distributed Training and Data Resources on Blue Waters

Aaron Saxton from NCSA gave this talk at the Blue Waters Symposium. “Blue Waters currently supports TensorFlow 1.3, PyTorch 0.3.0 and we hope to support CNTK and Horovod in the near future. This tutorial will go over the minimum ingredients needed to do distributed training on Blue Waters with these packages. What’s more, we also maintain an ImageNet data set to help researchers get started training CNN models. I will review the process by which a user can get access to this data set.”

Call for Applications: NCSA GPU Hackathon in September

NCSA is now accepting team applications for the Blue Waters GPU Hackathon. This event will take place September 10-14, 2018 in Illinois. “General-purpose Graphics Processing Units (GPGPUs) potentially offer exceptionally high memory bandwidth and performance for a wide range of applications. A challenge in utilizing such accelerators has been learning how to program them. These hackathons are intended to help overcome this challenge for new GPU programmers and also to help existing GPU programmers to further optimize their applications – a great opportunity for graduate students and postdocs. Any and all GPU programming paradigms are welcome.”

Using Ai to detect Gravitational Waves with the Blue Waters Supercomputer

NASA researchers are using AI technologies to detect gravitational waves. The work is described in a new article in Physics Review D this month. “This article shows that we can automatically detect and group together noise anomalies in data from the LIGO detectors by using artificial intelligence algorithms based on neural networks that were already pre-trained to classify images of real-world objects,” said research scientist, Eliu Huerta.

Supercomputing Graphene Applications in Nanoscale Electronics

Researchers at North Carolina State University are using the Blue Waters Supercomputer to explore graphene’s applications, including its use in nanoscale electronics and electrical DNA sequencing. “We’re looking at what’s beyond Moore’s law, whether one can devise very small transistors based on only one atomic layer, using new methods of making materials,” said Professor Jerry Bernholc, from North Carolina University. “We are looking at potential transistor structures consisting of a single layer of graphene, etched into lines of nanoribbons, where the carbon atoms are arranged like a chicken wire pattern. We are looking at which structures will function well, at a few atoms of width.”

Supercomputing Better Tools for Long-Term Crop Prediction

Researchers are using the Blue Waters supercomputer to create better tools for long-Term crop prediction. “We built this new tool to bridge these two types of crop models combining their strengths and eliminating the weaknesses. This work is an outstanding example of the convergence of simulation and data science that is a driving factor in the National Strategic Computing Initiative announced by the White House in 2015.”

Video: Deep Learning for Real-Time Gravitational Wave Discovery

Scientists at NCSA have pioneered the use of GPU-accelerated deep learning for rapid detection and characterization of gravitational waves. This new approach will enable astronomers to study gravitational waves using minimal computational resources, reducing time to discovery and increasing the scientific reach of gravitational wave astrophysics.

Dark Energy Survey Releases First Three Years of Data

Today scientists from the Dark Energy Survey (DES) released their first three years of data. This first major release of data from the Survey includes information on about 400 million astronomical objects, including distant galaxies billions of light-years away as well as stars in our own galaxy. “There are all kinds of discoveries waiting to be found in the data. While DES scientists are focused on using it to learn about dark energy, we wanted to enable astronomers to explore these images in new ways, to improve our understanding of the universe,” said Dark Energy Survey Data Management Project Scientist Brian Yanny of the U.S. Department of Energy’s Fermi National Accelerator Laboratory.