Troy, N.Y. — Lawrence Livermore National Laboratory (LLNL) and Rensselaer Polytechnic Institute will combine decades of expertise to help American industry and businesses expand use of high performance computing (HPC) under a recently signed memorandum of understanding.
“It’s well recognized that HPC is key to accelerating technological innovation and to fueling a nation’s economic vitality,” says Fred Streitz, director of LLNL’s High Performance Computing Innovation Center (HPCIC), which facilitates computational engagements with industry. “Our long, fruitful history of collaboration and joint scientific and technological discovery with RPI is a natural platform on which to build opportunities for companies to advance through the use of HPC.”
Livermore and Rensselaer will look to bridge the gap between the levels of computing conducted at their institutions and the typical levels found in industry. Scientific and engineering software applications capable of running on HPC platforms are a prime area of interest.
New “Balanced” Supercomputing System at Rensselaer Polytechnic Institute—the Most Powerful University-Based Supercomputer in New York State and the Northeast—Positions the University for Continued Leadership and Impact in Massively Parallel Computational and Data Analytics Research, Innovation, and Education
Rensselaer Polytechnic Institute today unveiled a new petascale supercomputing system, the Advanced Multiprocessing Optimized System, or AMOS.
With the ability to perform more than one quadrillion (1015) calculations per second, AMOS is the most powerful university-based supercomputer in New York state and the Northeast, and among the most powerful in the world. In addition to massive computational power, AMOS has high-performance networking capabilities with a bandwidth of more than four terabytes per second—more than the combined bandwidth of 2 million home Internet subscribers.
Rensselaer Polytechnic Institute Professor and Council co-Chair of the international Research Data Alliance Francine Berman joined with Google Vice President Vint Cerf to discuss the future of public access to research data in a Science magazine Op Ed appearing Aug 9. “Who Will Pay for Public Access to Research Data?” appears in the Policy Forum section of Science – a publication of the American Association for the Advancement of Science – and discusses the growing call for greater public access to data resulting from taxpayer sponsored research.
Suvranu De Named Fellow of U.S. Association for Computational MechanicsMay 30, 2017 -
Suvranu De, the J. Erik Jonsson ’22 Distinguished Professor of Engineering and head of the Department of Mechanical, Aerospace, and Nuclear Engineering, has been selected as a fellow of the U.S. Association for Computational Mechanics.
IBM and Rensselaer Team To Research Chronic Diseases With Cognitive ComputingMay 17, 2017 -
Graduate Engineering Programs Ranked 39th in the NationMarch 27, 2017 -
The graduate programs in engineering at Rensselaer Polytechnic Institute are once again considered among the best in the United States, according to the U.S. News & World Report Best Graduate Schools rankings released last week. For the third year in a row Rensselaer’s graduate engineering programs have been ranked 39th in the nation.
In The Media
IBM Pushes Deep Learning with a Watson UpgradeJuly 31, 2015 -
“A key challenge for modern AI is putting back together a field that has almost splintered among these methodologies,” says James Hendler, director of the Rensselaer Polytechnic Institute for Data Exploration and Applications in Troy, New York. RPI has access to an early version of Watson donated to the university by IBM, and Hendler teaches courses based on the technology.
Neuromorphic Processors Leading a New Double LifeApril 16, 2015 -
A team of researchers at the Rensselaer Polytechnic Institute led by Christopher Carothers, Director of the institute’s Center for Computational Innovations described for The Platform how True North is finding a new life as a lightweight snap-in on each node that can take in sensor data from the many components that are prone to failure inside, say for example, an 50,000 dense-node supercomputer (like this one coming online in 2018 at Argonne National Lab) and alert administrators (and the scheduler) of potential failures This can minimize downtime and more important, allow for the scheduler to route around where the possible failures lie, thus shutting down only part of a system versus an entire rack.
A clearer viewJanuary 6, 2015 -
... in Bolton Landing, Rick Relyea sat in comfortable new conference room at RPI's Darrin Freshwater Institute, using a massive video screen to demonstrate what is called the "data visualization laboratory."
Here is where lake, stream and weather data drawn from a network of up to 40 sensors, once crunched in massive computers, will be turned into graphic displays to explain how the 32-mile lake behaves and how it might change if some troubling trends continue. Surface sensors are connected to the lab via cellphone signal.