Rensselaer Researchers Receive $2.65 Million NSF…
Rensselaer Researchers Receive $2.65 Million NSF Grant To Install Balanced, Green Supercomputer at CCNI Supercomputing Center
A new system to be installed at the Rensselaer Polytechnic Institute supercomputing center will enable exciting new research possibilities across the nation and boost the university’s international leadership in computational modeling and simulation, data science, high-performance computing, and web science.
Funded by a $2.65 million grant from the National Science Foundation (NSF) and with additional support from Rensselaer and its Computational Center for Nanotechnology Innovations (CCNI), the new system will be a national resource for researchers in academia and industry across a wide range of disciplines. The system, scheduled to be delivered and installed in 2012, provides a balanced combination of computational power, fast data access, and visualization capabilities. It will be comprised of a powerful IBM Blue Gene/Q supercomputer, along with a multiterabyte memory (RAM) storage accelerator, petascale disk storage, rendering cluster, and remote display wall systems.
“The IBM Blue Gene/Q system is brand new, and should enable unprecedented innovations in massively parallel computing for data-intensive and multiscale research,” said Christopher Carothers, professor in the Department of Computer Science at Rensselaer, and lead researcher on the new grant. “Many important research projects are hitting a bottleneck, as the amount of data they’re generating continues to grow, as does their need to interact with this data. With our new balanced system, paired with the expertise of Rensselaer faculty and students, we should be able to help researchers in academia and industry to overcome many of these challenges.”
At Rensselaer, many research projects are poised to benefit from the new system. These projects include developing new methods for the diagnosis of breast cancer using data from non-invasive techniques; modeling plasmas to aid the design and safety of future fusion reactors; modeling wind turbine design to increase efficiencies and reduce maintenance; application of new knowledge discovery algorithms to very large semantic graphs for climate change and biomedical research, modeling heat flow in the world’s oceans, integrating data and computations across scales to gain a better understanding of biological systems and improve health care; and many others.
Time on the new system will be available to researchers nationwide. An allocation committee will be formed to assess proposals, on the basis of scientific merit, fit to the machine’s capabilities, and the potential to broaden the system’s user community and range of research. Rensselaer scientists and engineers also anticipate collaborations that will develop and apply the new techniques that will help researchers take advantage of this machine’s unique capabilities.
“Researchers at Rensselaer have developed highly scalable techniques that allow modeling to be done across hundreds of thousands of processors. This machine will further that research and provide a platform to explore new techniques that will be broadly applicable to exascale computing,” said Mark Shephard, professor in the department of Mechanical, Aerospace, and Nuclear Engineering (MANE) and director of the Scientific Computation Research Center at Rensselaer.
Experts in academia and industry anticipate realizing exascale computing — performing 1018 calculations per second — by the end of the decade. Exascale machines will be more than 100 times the computational power of today’s largest machines. The new Blue Gene/Q system at Rensselaer will be a first stop for many researchers looking to scale up their research over the next decade. Once researchers prove their project works on this system, they will well positioned to migrate to peta- and eventually exascale systems, including the large Blue Gene/Q systems due to be installed next year at two national laboratories.
Rensselaer faculty and students will benefit greatly by working on these projects, said CCNI Director James Myers. Since opening in 2007 as the world’s seventh largest computer, CCNI has helped researchers at Rensselaer and around the country tackle scientific and engineering problems ranging from the modeling of materials, flows, and microbiological systems, to the development of entirely new simulation technologies. More than 700 researchers, faculty, and students from 50 universities, government laboratories, and companies have run high-performance science and engineering applications at CCNI.
“The resources we have available at CCNI have enabled researchers to work at the forefront in the development of scalable computing techniques and in the application of computing to some of the most challenging problems in academia and industry. We’re delighted to have the opportunity with this new machine to continue and expand Rensselaer’s support of leading-edge research and the development of the tools and expertise that will be required to realize the potential of next-generation computer systems,” Myers said. “With the rapid changes in computing architecture and the increasing breadth in how they’ll be applied, resources like this are critical for training the next generation of scientists and engineers.”
Along with Carothers, Myers, and Shephard, co-investigators on the grant are: Peter Fox, professor in the Department of Earth and Environmental Sciences and a Tetherless World Constellation chair at Rensselaer; and Lucy Zhang, associate professor in MANE.
Contact: Michael Mullaney firstname.lastname@example.org 518-276-6161 Rensselaer Polytechnic Institute