World-Class Science Through World Leadership in HPC

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Proposal: 0622780 PI Name: Boisseau, John R.ABSTRACTThis award is for the acquisition, deployment and operation of a high-performance computational system for use by the broad science and engineering research and education community. The system, to be known as the Sun Constellation Cluster, will be deployed at the Texas Advanced Computing Center, located at the University of Texas at Austin. The project represents a collaboration between the University of Texas at Austin, Sun Microsystems, Advanced Micro Devices, the Cornell Theory Center at Cornell University, and the Fulton High Performance Computing Institute at Arizona State University. The Sun Constellation Cluster will greatly increase the combined capacity of the computational resources of the current NSF-funded, shared-use, high-performance computing facilities and provide a capability that is an order of magnitude larger than the largest supercomputer that NSF currently supports. Because of this, it will advance research and education across a broad range of topical areas in science and engineering that use high-performance computing to advance understanding. With this new resource, researchers will study the properties of minerals at the extreme temperatures and pressures that occur deep within the Earth. They will use it to simulate the development of structure in the early Universe. They will probe the structure of novel phases of matter such as the quark-gluon plasma. Such computing capabilities enable the modeling of life cycles that capture interdependencies across diverse disciplines and multiple scales to create globally competitive manufacturing enterprise systems. The system will permit researchers to examine the way proteins fold and vibrate after they are synthesized inside an organism. Sophisticated numerical simulations will permit scientists and engineers to perform a wide range of in silico experiments that would otherwise be too difficult, too expensive or impossible to perform in the laboratory. High-performance computing of the sort that will be possible with the new system is also essential to the success of research and education conducted with sophisticated experimental tools. For example, without the waveforms produced by numerical simulations of black hole collisions and other astrophysical events, gravitational wave signals cannot be extracted from the data produced by the Laser Interferometer Gravitational Wave Observatory; high-resolution seismic inversions from the higher density of broadband seismic observations furnished by the EarthScope project are necessary to determine shallow and deep Earth structure; simultaneous integrated computational and experimental testing is conducted on the Network for Earthquake Engineering Simulation to improve seismic design of buildings and bridges; and advanced computing capabilities will be essential to extracting the signature of the Higgs boson and supersymmetric particles, two of the scientific drivers of the Large Hadron Collider, from the petabytes of data produced in the trillions of particle collisions. This project presents an exciting opportunity to advance the type of research described above by: (i) greatly extending the capacity of high-performance computational resources available to the science and engineering communities, (ii) extending the range of advanced computations that can be handled by providing a system with a very large amount of memory, and a very large amount of processing capability. This system will use an architecture that is similar to that present in many academic institutions and to which many science and engineering applications have been ported. In addition, the system represents an important stepping-stone towards the goal of the use of petascale computing in science and engineering research and education at the end of the decade. It will provide a platform that will allow researchers to experiment with techniques for overcoming one of the hurdles in the path to petascale computing, scaling to very large numbers of processors. This computing system will also provide opportunities to many graduate students and post-docs to gain experience in using high-performance computing systemsThe Texas Advanced Computing Center and its partners will broaden the impact of the computing resource by: teaching in situ and online classes for undergraduate and graduate students in high-performance computing, visualization, data analysis, and grid computing for computational research in science and engineering; partnering with faculty and students at a number of Minority Serving Institutions to provide training in the use of high-performance computing resources; and collaborating with the Girlstart program, a program that supports and enhances the interest of girls in math, science, and technology.