Amy McGovern, associate professor in the School of Computer Science and adjunct professor in the School of Meteorology at the University of Oklahoma, is leading a research team in an investigation that combines high-performance computing and meteorology to develop models and simulations for advancing tornado-prediction capabilities. In a recent article, McGovern and research team member Brittany Dahl, an OU meteorology graduate student who is completing her master’s thesis under McGovern’s supervision, describe how the Kraken and Nautilus supercomputers are essential to their efforts. Read more on the NICS website.
Worldwide, buildings are major energy consumers. In the U.S., for example, they use 41 percent of the nation’s primary energy; and in countries across the globe, the building energy consumption is similar, ranging from 30 percent to 40 percent. One way to improve the energy efficiency of buildings is computer modeling and simulation, but getting energy models right is difficult. A research team at Oak Ridge National Laboratory—with HPC assistance from RDAV/NICS and an XSEDE allocation on the Nautilus supercomputer—has developed a calibration methodology to solve the problem. Read more on the NICS website.
Many research problems in science and engineering rely on both interdisciplinary knowledge and sophisticated computing. The Remote Data Analysis and Visualization (RDAV) Center seeks motivated undergraduate students who are eager to take on these challenges by using high performance computing to attack research problems in the biological, physical, social, computing, or engineering sciences. We have opportunities for the summer of 2013 at all stages of the data analysis process: From preparing raw data, to using and developing data analysis and visualization processes and tools, to deploying web-based interfaces for interacting with the results.
Our center works with researchers who are tackling a wide range of problems including extracting meaning through text mining, understanding biodiversity, making sense of the universe, and developing visualization tools. We seek students with a passion for real-world problems, an understanding of science or engineering, and the computer science skills to make it happen. Ideal students will be majoring in a science or engineering discipline with a strong background in computer science; students in all majors and from all backgrounds will be considered. We highly encourage applications from students from under-represented groups.
RDAV is a joint project between several institutions. We expect to have opportunities available at our main offices at the University of Tennessee’s Joint Institute for Computational Sciences in Knoxville and Oak Ridge, TN as well as at the Lawrence Berkeley Laboratory (LBL) in Berkeley, CA. The positon at LBL requires skills in C/C++, Python, and HTML5; WebGL is optional for this position.
To apply, please send the following to Dr. Amy Szczepanski at email@example.com:
1. Personal statement (250-500 words) describing your interest in and qualifications for this position.
2. Resume or CV.
3. Contact information of a professor who would be willing to support your application
Please send all documents in plain text (.txt), rich text (.rtf), or PDF format.
4. Which location(s) you are interested in working at.
For highest priority, apply by Monday, February 11. We will continue to review all applications until all positions are filled. Compensation will be determined by the policies of each host institution, and dates of employment will be arranged by the student and the supervisor. Students must be able to legally work in the United States.
RDAV is managed by the University of Tennessee with the National Institute for Computational Sciences and has its main offices on the campus of the Oak Ridge National Laboratory in Oak Ridge, TN and at the University of Tennessee, Knoxville. RDAV is a collaboration between UT and the Lawrence Berkeley Laboratory, the Oak Ridge National Laboratory, the National Center for Supercomputing Applications, the University of Wisconsin, Rutgers University, Emory University, and the Georgia Institute of Technology.
The University of Tennessee is an EEO/AA/Title VI/Title IX/Section 504/ADA/ADEA institution in the provision of its education and employment programs and services. All qualified applicants will receive equal consideration for employment without regard to race, color, national origin, religion, sex, pregnancy, marital status, sexual orientation, gender identity, age, physical or mental disability, or covered veteran status.
MATLAB 2012b has been installed on Nautilus, and is ready for testing by users. When using MATLAB on Nautilus, be sure to load the correct module for the version that you would like to use.
It is important to note that MATLAB 2012b on Nautilus will only work from within the batch system. In order to use MATLAB 2012b interactively, be sure to launch an interactive batch job with the -I option before launching MATLAB.
Collaborative work performed by the Remote Data Analysis and Visualization Center (RDAV) and University of Tennessee (UT), Knoxville, artist Evan Meaney that examines the interplay of data, information, and knowledge has won the jury prize for the Distributed Microtopias exhibition at the 15th Annual Finger Lakes Environmental Film Festival (FLEFF).
The RDAV–Meaney collaborative project, entitled “Null_Sets,” is a collection of artwork that visualizes the size and structure of data. The artwork was created using an open-source script developed at RDAV with which whole bodies of text, from classic literature to HTML to genomic data, can be exported as digital images.
“In a gallery, we can analyze these data sets side by side and consider the differences between, say, Moby Dick and an X-chromosome,” Szczepanski said. “Our method relies on an encoding that represents the changes in pixel color and intensity, and might be adapted to explore how values in a dataset change.”
“Null_Sets explores the gap between data and information,” Meaney said. “This project makes it possible to visualize both the size and architecture of large-scale data sets through an aesthetic lens.”
The novel use of encoding employed by Null_Sets coincides with the focus of this year’s FLEFF, the exploration of what it terms “Distributed Microtopias” and defines as projects that “run across distributed networks like the Internet to provoke and educate from remote locations on a sustainable scale, expand knowledge rather than contain it, invite participation and exploration, and unhinge familiar habits of thinking to envision new possibilities for historical and cultural clarity.”
The project took shape in the spring of 2010 when Szczepanski, searching for digital media artists with whom RDAV could collaborate, contacted Meaney under the advice of UT’s visual arts committee.
After discussing Null_Sets and the theory behind it with Meaney, Szczepanski wrote the initial code, and then a student assumed the task. As project designer and director, Meaney suggested revisions to the code to improve the work, chose the texts, handled tasks related to producing physical images, made submissions to shows and festivals, and printed catalogs, Szczepanski said.
“The techniques we developed in this project laid the groundwork for a larger project that will likely use the Nautilus supercomputer in the future,” she said.
Nautilus is managed for the National Science Foundation by the National Institute for Computational Sciences (NICS).
Support for the Null_Sets project came from the National Science Foundation, UT, the Joint Institute for Computational Sciences, NICS, Oak Ridge National Laboratory, Jian Huang of Seelab, Dorothy Habel of the UT-Knoxville School of Art, and Mike Berry of Project Gutenberg.
Null_Sets consists of a set of images plus a free application and can be accessed here. Project Gutenberg, a producer of free ebooks, is a resource for text that can be used with the Null_Sets application.
More information on the Distributed Microtopias Exhibition for FLEFF can be accessed here.
RDAV is the University of Tennessee’s Center for Remote Data Analysis and Visualization, sponsored by the National Science Foundation as part of the XSEDE project. RDAV is a partnership between the National Institute for Computational Sciences, ORNL, Lawrence Berkeley National Laboratory, the University of Wisconsin, the National Center for Supercomputing Applications at the University of Illinois, Emory University, Rutgers University, and the Georgia Institute of Technology.