HPCwire: LSU Professor Receives NSF Award to Develop Stork Data Scheduler

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September 03, 2009

LSU Professor Receives NSF Award to Develop Stork Data Scheduler

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BATON ROUGE, La., Sept. 3 -- LSU Professor Tevfik Kosar received a half-million dollar grant from the National Science Foundation to support his work on Stork Data Scheduler, an innovative computing tool that helps researchers access and transfer large data sets easily and efficiently.

The grant award provides Kosar, a professor with the LSU Department of Computer Science who holds a joint appointment with the LSU Center for Computation & Technology, or CCT, with funding for three years to further develop and enhance the Stork Data Scheduler.

As computational science applications expand and become increasingly complex, researchers using these applications are generating larger and larger amounts of data, sometimes up to hundreds of terabytes and even petabytes. Sharing, disseminating, and analyzing these large data sets is a growing challenge for researchers, who need to collaborate but are unable to move so much information quickly or effectively.

Even though many researchers now have access to regional high-speed, fiber optic networks such as the Louisiana Optical Network Initiative, or LONI, many users cannot obtain even a fraction of the theoretical speeds these networks promise because of data overload, which slows transmission and causes a bottleneck in computational performance and reliability.

Kosar's project, funded through the National Science Foundation's Strategic Technologies for Cyberinfrastructure Program, aims to ease data bottlenecks, which will improve high-performance computing systems' performance. Stork, so named because it delivers data, is a batch scheduler program that makes it easier for researchers to share, store and deliver data across these systems.

Using Stork, researchers can transfer very large data sets with only a single command, making it one of the most powerful data transfer tools available. Stork is compatible with advanced high-performance computing toolkits, and researchers can use the software to access the power of these large systems and use them more effectively.

"The Stork data scheduler makes a distinctive contribution to the computational research community because it focuses on planning, scheduling, monitoring and management of data," Kosar said. "Unlike existing approaches, Stork treats data resources and their related tasks as primary components of computational resources, not simply as side effects. This will lead to quicker and more effective collaboration among researchers."

Researchers consider the Stork Data Scheduler a highly transformative project because of its potential to dramatically change how scientists perform their research and to rapidly facilitate sharing of experience, raw data, and results. Future applications could rely on Stork to manage storage and data movement reliably and transparently across many systems, eliminating the unnecessary failure of distributed tasks.

The Stork team made the first version (Stork 1.0) available for download through the Stork project Web page, www.storkproject.org, in December 2008. Stork is open source, and users can download it for free.

Data storage and management is Kosar's research specialty at the University. In 2006, he received a $1 million grant from NSF to create advanced data archival, processing and visualization capabilities across the state through the PetaShare project (www.petashare.org).

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