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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.

Advanced Protein Prediction Using Deep Learning on Blue Waters Supercomputer

Researchers at NCSA used the Blue Waters Supercomputer and Deep Learning to achieve a breakthrough in protein structure predictions. As published in the Cell Systems journal, the research was conducted by Jian Peng, NCSA Faculty Fellow and Assistant Professor in the Department of Computer Science at Illinois and Yang Liu, a graduate student in the Department of Electrical and Computer Engineering. “Peng’s research proposes to largely explore a more accurate function for evaluating predicted protein structures through his development of the deep learning tool, DeepContact. DeepContact automatically leverages local information and multiple features to discover patterns in contact map space and embeds this knowledge within the neural network. Furthermore, in subsequent prediction of new proteins, DeepContact uses what it has learned about structure and contact map space to impute missing contacts and remove spurious predictions, leading to significantly more accurate inference of residue-residue contacts.”

Blue Waters Supercomputer Crunches Data from NASA’s Terra Satellite

Researchers are using the Blue Waters supercomputer at NCSA to process new data from NASA’s Terra Satellite. Approximately the size of a small school bus, the Terra satellite explores the connections between Earth’s atmosphere, land, snow and ice, ocean, and energy balance to understand Earth’s climate and climate change and to map the impact of human […]

SC17 Panel: Energy Efficiency Gains From Software

In this video from SC17 in Denver, Dan Reed moderates a panel discussion on HPC Software for Energy Efficiency. “This panel will explore what HPC software capabilities were most helpful over the past years in improving HPC system energy efficiency? It will then look forward; asking in what layers of the software stack should a priority be put on introducing energy-awareness; e.g., runtime, scheduling, applications? What is needed moving forward? Who is responsible for that forward momentum?”

HPC in Agriculture: NCSA and Syngenta’s Dynamic Partnership

In this video, Jim Mellon from Sygenta describes how the company’s partnership with NCSA is helping the company answer the agricultural challenges of the future. “Together, we’re solving some of the toughest issues in agriculture today, like how to feed our rapidly growing population knowing that the amount of land we have for growing crops is finite. NCSA Industry provides the HPC resources that Syngenta’s scientists need to solve these issues, as well as an industry focus on security, performance, and availability, with the consultancy to better understand how to maximize these resources.”