SAN JOSE, Calif. -- BlueArc Corporation, a leader in scalable, high-performance unified network storage, today announced that the Rosen Center for Advanced Computing at Purdue University has deployed a Titan 2000 network storage system to act as a key infrastructure component supporting the universitys critical research computation. With the Titan in place, the center is able to handle the massive data sets generated by scientists' advanced research in life science and climate modeling, and scale its storage to accommodate a large number of clients.
We dont have a great deal of predictability and we dont know what is going to happen day to day, so we need something that gives us a lot of flexibility on performance. Small databases, large files, we dont know what will come our way, said Bruce Loftis, managing director of the Rosen Center for Advanced Computing, Purdue University. "We needed a solution that can scale high in storage capacity, but also handle hundreds of nodes simultaneously."
The Rosen Center is part of Purdue Universitys overall IT organization, which centrally manages and administers information technology important to the Universitys day-to-day business functions as well as research and teaching activities. A wide range of applications requires that the center develop and maintain a storage system that is flexible enough to excel at both large files and small files, reads and writes. Aggressive research initiatives related to remote sensing, climate modeling and nanotechnology are among the diverse range of high-performance computing applications and data sets that are driving storage requirements.
As a result of its integration of the Titan, the Rosen Center expects to dramatically improve the flexibility and scalability of its storage system, allowing thousands of scientists, faculty members and graduate students to run simulations and conduct sophisticated analysis. For instance, the Titan will enable the Universitys life science researchers to process massive amounts of information from their projects' robotic and digital instrumentation, with confidence that performance should not be compromised by increases in sample frequency and data runs.