Parallel Computing at the National Cancer Institute Parallel Computing & Computational Ecology at UCSB & NCEAS Star-P at San Diego Supercomputer Center   Parallel Computing at Whitehead MIT Bio-Imaging Institute   What Customers Say What Partners Say What Investors Say

What Customers Say

"Researchers have struggled to create a consistent mathematical framework for valuation, market risk and opportunities in corporate credit. With Star-P, not only can we create accurate, realistic models and compute the answers we need quickly, we can continually experiment with new algorithms and models with real-time interactivity. "

Peter Cotton
CEO of Julius Finance

"We were not able to generate images with such a fine sampling pitch until we used Star-P. It takes a huge amount of memory and computational resources to execute the algorithm. Typical resolution for ultrasound imaging systems is in the 200-300 micron range. With Star-P, we were able to tap into the University's supercomputing clusters to generate ultra high resolution images of 67 microns, without having to become parallel programming experts. "

Francesco Viola
University of Virginia (U.Va.) School of Engineering and Applied Science

"To stay competitive in science and engineering industries, the U.S. needs easy to use programming platforms that can tap into HPC resources without having to become a parallel programming expert. Star-P combined with the Blue Collar Computing initiative is a great platform for making our HPC resources accessible to a much broader base of users, which is our organization's key mission. "

Ashok Krishnamurthy
Ohio Supercomputer Center

"Accelerating computational processes associated with data mining and modeling enables us to find problems, optimize and ultimately refine these models more quickly. Creating the best possible computational models in the shortest time gives us significant predictive power and improves the effectiveness of experimental work. "

James G. Evans
Research Scientist for Imaging and Informatics
Computational and Systems Biology Initiative, M.I.T.

"The graph toolbox allows researchers who are not experts in the field of combinatorial scientific computing to leverage its methods in their own research "

Viral Shah
University of California, Santa Barbara

"OSCAR is a powerful NASA resource that can now be extended with Star-P to a wider range of scientists whose work demands high performance computing, but who are not parallel programming experts. Scientists increasingly need more processing power beyond what their desktops provide, but the complexities of programming parallel systems have kept HPC servers out of reach. With Star-P, they can continue work with the interactive desktop tools that they prefer while seamlessly tapping into HPCs for the heavy computational tasks."

Anthony Gualtieri
Global Science & Technology, Inc.

"Star-P lets our scientists continue to work with their preferred tools, shielding them from the programming complexities of parallel systems. It automatically connects MATLAB® to the server and parallelizes the application code on the fly."

Bryan Wong
Department of Chemistry
Massachusetts Institute of Technology

"National Cancer Institute is accustomed to working in MATLAB® and with certain formatted files, and the Star-P approach retains that environment. If your goal is to take the same interactive environment and transfer it to a parallel processing system with a lot more memory, then you’ll look for the easiest way to get there."

Dr. Mark Potts
HPC Applications, Inc.

"Star-P is working really well and has managed some pretty impressive calculations, like inverting a 14 GB matrix in only 40 minutes on 16 processors! And has reduced run times of 30 minutes to 30 seconds for some CSIRO [Commonwealth Scientific and Industrial Research Organisation] researchers, and improved results at the same time. The code adjustments have been minimal to get it working."

Andrew Meijers, University of Tasmania

“Our molecular models involve computations with 20,000x20,000 matrices, so we quickly reached the limits of desktop memory and computing power.  We are looking to Star-P to let us continue working interactively within our MATLAB® environment, extending our computations to larger and more complicated models.”

Bryan Wong, Researcher, M.I.T. – Earth, Atmospheric and Planetary Sciences, Joint project with National Center for Supercomputing Applications (NCSA)

“We view Star-P as a major productivity tool to support D.O.D. customers.  Rather than re-coding algorithms in C or Fortran and MPI, Star-P lets us continue working in the high productivity desktop MATLAB® environment, while scaling to supercomputers.”

John Nehrbass, PhD, Director, Computational Signal and Image Processing, Ohio Supercomputer Center / Wright-Patterson AFB

“Star-P has dramatically accelerated the development of microwave image reconstruction algorithms by allowing us to stay within the MATLAB® programming environment and exploit supercomputing resources for algorithm development and processing throughput. It’s an enabler – without it we would not be using parallel hardware, and the increased capabilities fundamentally transform what we are able to do in the Advanced Radar Waveforms & Processing Branch.”

Electronics Engineer, Air Force Research Labs

“Where traditional radar images might measure 10 megabytes, satellite radar can easily inundate a facility with terabytes of data daily, dramatically complicating and delaying the analysis process. Satellite radar can't help our military readiness if we have to wait a long time for the analysis results. With Star-P, researchers can now preserve their familiar workflow while tackling data sets an order of magnitude larger than they process on their desktops.”

Mark Barnell Air Force Research Labs

“Our performance and reliability simulations of ground vehicles are run many times with a wide range of parameters, and a wide range of operational conditions, which often takes more time to compute than we can afford to wait for. Serial computer runs are not the answer. Making parallelization easy for the typical analyst is essential. We needed a solution to convert existing serial code into parallel code quickly and easily. If successful, Star-P will enable TARDEC users who are unfamiliar with parallel computing to speed up very large simulations, without having to re-program their models.”

Dr. David Gorsich, Senior Research Scientist, U.S. Army TARDEC

“Researchers tackling problems on a desktop environment can only use phantom data sets or synthetic data. This project will ultimately empower users to scale to exploring real data sets that can be processed on large parallel servers with many processors and large distributed memory systems, all within the comfort of their preferred desktop modeling tool.”

Dr. David Kaeli on using Star-P as a testing platform for the project, Research Thrust Leader, NSF Center for Subsurface Sensing and Imaging Systems, Northeastern University

What Partners Say

“We are very excited about working with ISC to bring Star-P to the market.  This breakthrough application, in combination with SGI’s high performance and scalable Linux systems, will give our customers a faster path to new science, making unprecedented interactive computing power accessible via inside their favorite desktop tools.”

Dave Parry, Senior Vice President and General Manager, Server and Platform Group,
Silicon Graphics, Inc.

“Having been a developer of several generations of strong scalable systems, I've been disappointed by the small impact HPC has had on the average scientist or engineer, mainly due to the limited availability of applications.  As a society, we have many pressing problems (for example, deaths due to tsunamis, hurricanes, and AIDS, illness due to malaria and possibly avian flu, and terrorist attacks) that parallel computing could play an integral role in solving, and yet its impact on those problems is modest.  Star-P enables 10X more scientists and engineers to use HPCs through a straightforward process, expanding the impact of HPCs on societal challenges.”

Steve Reinhardt, Principal Engineer, Silicon Graphics, Inc.

“We were able to easily interface to Star-P the Trilinos software framework and library, which provides broad-ranging high-performance capabilities for solving numerical systems at the heart of many complex multiphysics applications. This dramatically expands the range of solvers and computing power that users can leverage.”

Ken Stanley, 500 Software

“We are excited by the opportunity to bring to the research community a new breakthrough technology that will let scientists and other technical users who work with desktop simulation tools tap the power of parallel computing without having to re-program their code. Star-P provides easy, automatic parallelization of both new and existing codes, enabling our customers to achieve faster time to discovery. It's the first solution we've seen that turns parallel supercomputers into truly interactive tools.”

Tom Mountcastle, President, James River Technical

What Analysts Say

“Based on recent IDC market studies, end-users won't be able to realize the full promise of high performance computing hardware until scientists, engineers or researchers can more easily program applications to run on parallel architectures.  Star-P is designed to address this problem by focusing on making parallel programming an interactive approach.”

Earl Joseph, IDC Research Vice President and Executive Director, HPC User Forum

“Scientists and engineers are looking for easier and better ways to advance their science, which often requires new programming models like Star-P in order to take advantage of HPC cluster systems. HPC cluster systems have become the fastest growing IT sector, with growth rates exceeding 70 percent over each of the last four years, and HPC users are constantly looking for ways to make better use of these systems.”

Earl Joseph, IDC Research Vice President and Executive Director, HPC User Forum

What Investors Say

“Up to now, scientists and engineers not only had to spend a lot of time and energy to solve some of their most complex problems but also had to spend even more time creating custom software for parallel processing to allow their computers to handle these jobs.  With the Star-P platform, ISC allows these experts to focus on their jobs by putting parallel processing at their fingertips. ISC has created a new category in the rapidly evolving multi-billion dollar technical computing market.  Parallel computing is becoming mainstream, and ISC is ideally positioned to ride this wave.”

James Geshwiler, Managing Director, CommonAngels

“Computer vendors are now delivering massive and affordable computing power to technical computing users, but it is difficult to exploit this power due to programming complexities. ISC is delivering a solution which allows engineers, scientists and analysts to easily take advantage of this computing power.”

Ed Kania, Managing Director and Chairman Flagship Ventures

“This M.I.T.-born technology is enabling scientists and engineers to finally take advantage of the world’s most powerful computers to solve the complex problems, without wasting time creating custom software for parallel processing systems. Parallel computing is becoming mainstream, and ISC is ideally positioned to ride this wave.”

Dennis Costello, Managing Director Rock Maple Ventures