LARGE SCALE PROBLEM SOLVING USING AUTOMATIC CODE GENERATION AND DISTRIBUTED VISUALIZATION Academic Article

abstract

• 2010 SCPE. Scientific computation faces multiple scalability challenges in trying to take advantage of the latest generation compute, network and graphics hardware. We present a comprehensive approach to solving four important scalability challenges: programming productivity, scalability to large numbers of processors, I/O bandwidth, and interactive visualization of large data. We describe a scenario where our integrated system is applied in the field of numerical relativity. A solver for the governing Einstein equations is generated and executed on a large computational cluster; the simulation output is distributed onto a distributed data server, and finally visualized using distributed visualization methods and high-speed networks. A demonstration of this system was awarded first place in the IEEE SCALE 2009 Challenge.

authors

• Tao, Jian

published proceedings

• SCALABLE COMPUTING-PRACTICE AND EXPERIENCE

author list (cited authors)

• Hutanu, A., Schnetter, E., Benger, W., Bentivegna, E., Clary, A., Diener, P., ... Allen, G.

complete list of authors

• Hutanu, Andrei||Schnetter, Erik||Benger, Werner||Bentivegna, Eloisa||Clary, Alex||Diener, Peter||Ge, Jinghua||Kooima, Robert||Korobkin, Oleg||Liu, Kexi||Loffler, Frank||Paruchuri, Ravi||Tao, Jian||Toole, Cornelius||Yates, Adam||Allen, Gabrielle

publication date

• January 2010

published in

• Scalable Computing : Practice and Experience  Journal

keywords

• Computer Algebra Systems
• DISTRIBUTED SYSTEMS
• Data Intensive Applications
• High Performance Computing
• High Speed Networks
• Problem Solving Environment
• Scientific Visualization

start page

• 205

end page

• 220

volume

• 11

issue

• 2