ExM:System Support for Extreme-Scale, Many-Task Applications

Other · Tue May 31 00:00:00 EDT 2011

OSTI ID:1015459

Katz, Daniel S

The ever-increasing power of supercomputer systems is both driving and enabling the emergence of new problem-solving methods that require the effi cient execution of many concurrent and interacting tasks. Methodologies such as rational design (e.g., in materials science), uncertainty quanti fication (e.g., in engineering), parameter estimation (e.g., for chemical and nuclear potential functions, and in economic energy systems modeling), massive dynamic graph pruning (e.g., in phylogenetic searches), Monte-Carlo- based iterative fi xing (e.g., in protein structure prediction), and inverse modeling (e.g., in reservoir simulation) all have these requirements. These many-task applications frequently have aggregate computing needs that demand the fastest computers. For example, proposed next-generation climate model ensemble studies will involve 1,000 or more runs, each requiring 10,000 cores for a week, to characterize model sensitivity to initial condition and parameter uncertainty. The goal of the ExM project is to achieve the technical advances required to execute such many-task applications efficiently, reliably, and easily on petascale and exascale computers. In this way, we will open up extreme-scale computing to new problem solving methods and application classes. In this document, we report on combined technical progress of the collaborative ExM project, and the institutional financial status of the portion of the project at University of Chicago, over the rst 8 months (through April 30, 2011)

• Research Organization: The University of Chicago
• Sponsoring Organization: USDOE SC Advanced Scientific Computing Research (SC-21)
• DOE Contract Number: SC0005380
• OSTI ID: 1015459
• Report Number(s): DE-FC02-0ER26012; ER26012
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICS AND COMPUTING