Data and Computation Abstractions for Dynamic and Irregular Computations

Conference · Sat Dec 31 00:00:00 EST 2005

OSTI ID:881703

Krishnamoorthy, Sriram; Nieplocha, Jarek; Sadayappan, Ponnuswamy

Effective data distribution and parallelization of computations involving irregular data structures is a challenging task. We tackle the twin-problems in the context of computations involving block-sparse matrices. The programming model provides a global view of a distributed block-sparse matrix. Mechanisms are provided for the user to express the parallel tasks in the computation. Locality-aware load-balancing of the tasks ensures good scalability. The primitives are based on the Aggregate Remote Memory Copy Interface, and are inter-operable with the Global Arrays programming suite and MPI. Results are presented that demonstrate the utility of this approach.

• Research Organization: Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 881703
• Report Number(s): PNNL-SA-46884; KJ0101030; TRN: US200613%%16
• Resource Relation: Conference: Proceedings of the High Performance Computing-HiPC 2005. 12th International Conference. Published in Lecture Notes in Computer Science, 3769(258-269
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
DATA ANALYSIS
PERFORMANCE
PARALLEL PROCESSING
PROGRAMMING
COMPUTER CALCULATIONS
irregular data structures
block sparse matrices
parallel computing