Nov. 22, 2017 — The Global Initiative to Enhance @scale and Distributed Computing and Analysis Technologies (GECAT) project, led by the National Center for Supercomputing Applications (NCSA)’s NSF-funded Blue Waters Project, which seeks to build connections across national borders as a way of improving a global cyberinfrastructure for scientific advancement, has announced the funding of two seed projects that connect researchers on different continents to high performance computing resources that would not otherwise be attainable.
The first, newly-funded project, “High-End Visualization of Coherent Structures and Turbulent Events in Wall-Bounded Flows with a Passive Scalar” is led by Guillermo Araya (University of Puerto Rico) in collaboration with Guillermo Marin and Fernando Cucchietti (both of the Barcelona Supercomputing Center) and focuses on creating time-dependent, three-dimensional flow visualizations. As with most visual simulations, the amount of data required is massive and nearly impossible to sift through without robust parallel computing infrastructure. The GECAT enables this visualization to be possible by connecting Dr. Araya from the University of Puerto Rico with one of Europe’s strongest HPC centers, the Barcelona Supercomputing Center, in order to provide the parallel processes necessary to perform these intricate, data-intensive visualizations at a speed that would otherwise be impossible.
The second, a continuation of a previous GECAT pilot project titled “Performance Scalability and Portability on Advanced HPC Systems”, features William Tang (PI) of Princeton University in collaboration with James Lin (PI) of Shanghai Jiao Tong University (SJTU), who seek to improve the way code (specifically, GTC-P code) is used on modern GPU/CPU systems. Deploying this code in systems like Pi, a supercomputer housed at SJTU or the National Center for Supercomputing Applications’ (NCSA) Blue Waters system, will in-turn allow researchers to explore the code’s utility on GPU/CPU systems, and find ways to make this and similar codes more scalable and portable. This collaboration, enabled by GECAT, could help researchers develop and share associated lessons learned to assist to better develop and deploy their applications codes on GPU/CPU systems such as PI at SJTU and Blue Waters at NCSA.
The Global Initiative to Enhance @scale and Distributed Computing and Analysis Technologies (GECAT) project is part of the National Science Foundation’s Science Across Virtual Institutes (SAVI) program and is an extension of the NSF-funded Blue Waters project, which provides access to one of the world’s most powerful supercomputers and enables investigators to conduct breakthrough computational and big data research. GECAT is led by William Kramer, Blue Waters project director, and a research professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign and John Towns, NCSA’s executive director for science and technology, is a co-principal investigator and will help connect GECAT to the Extreme Science and Engineering Discovery Environment (XSEDE) project.
This GECAT supports International Virtual Research Organizations (IVROs) that promote and enable efficient collaboration and cooperation of researchers and developers in multiple countries by seeding the development of new, innovative cyberinfrastructure features enabling international scientific collaboration for scientific advances. The project directly supports the participation of multiple U.S. participants (senior and junior faculty, postdoctoral fellows, graduate students) in workshops, and to interact, communicate, and collaborate in small research and development “seed” projects with international partners from multiple countries in Europe and Asia. The GECAT budget allows for small awardsto US investigators initially for one year with possible extensions for additional years to be made for collaborative seed projects (travel, salary) who are attempting to create an IVRO. The funding is available to current XSEDE or Blue Waters users/PI’s.