High Performance Computing Issues for Grid Based Dynamic Data-Driven Applications
DDDAS creates a rich set of new challenges for applications,algorithms, systems software, and measurement methods.DDDAS research typically requires strong, systematic collaborations between applications domain researchers and mathematics, statistics, and computer sciences researchers,as well as researchers involved in the design and implementation of measurement methods and instruments.Consequently, most DDDAS projects involve multidisciplinary teams of researchers.DDDAS enabled applications run in a different manner than many traditional applications. They place different strains on high performance systems and centers due to dynamic and unpredictable changes in resources that are required during long term runs. An on demand environment is required. In this paper, we will also categorize many of these differences.
DDDAS HPC Dynamic scheduling Resource allocation Data centers Data filters Data assimilation
Craig C.Douglas Gabrielle Allen Yalchin Efendiev Guan Qin
Computer Science Department, University of Kentucky 773 Anderson Hall, Lexington, KY 40506-0046, USA Department of Computer Science and Center for Computation and Technology, Louisiana State University Institute for Scientific Computation, Texas A&M University, Address, 612 Blocker, 3404 TAMU, College
国际会议
杭州
英文
175-178
2006-10-12（万方平台首次上网日期，不代表论文的发表时间）