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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.”

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.

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 […]

NCSA Blue Waters Report Shows Economic Benefits of HPC

The importance of supercomputing on local and national economic prosperity has been highlighted by a recent study which reported that its Blue Waters project to be worth more than $1.08 billion for the Illinois’ economy. The study was completed by the published by the National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign.

Video: Overview of Scientific Workflows

Scott Callaghan from the Southern California Earthquake Center presented this talk as part of the Blue Waters Webinar Series. “I will present an overview of scientific workflows. I’ll discuss what the community means by “workflows” and what elements make up a workflow. We’ll talk about common problems that users might be facing, such as automation, job management, data staging, resource provisioning, and provenance tracking, and explain how workflow tools can help address these challenges. I’ll present a brief example from my own work with a series of seismic codes showing how using workflow tools can improve scientific applications.”

Video: An Overview of the Blue Waters Supercomputer at NCSA

In this video, Robert Brunner from NCSA presents: Blue Waters System Overview. “Blue Waters is one of the most powerful supercomputers in the world. Scientists and engineers across the country use the computing and data power of Blue Waters to tackle a wide range of challenging problems, from predicting the behavior of complex biological systems to simulating the evolution of the cosmos.”