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Title: On Overlapping Communication and File I/O in Collective Write Operation
Many parallel scientific applications spend a significant amount of time reading and writing data files. Collective I/O operations allow to optimize the file access of a process group by redistributing data across processes to match the data layout on the file system. In most parallel I/O libraries, the implementation of collective I/O operations is based on the two-phase I/O algorithm, which consists of a communication phase and a file access phase. This papers evaluates various design options for overlapping two internal cycles of the two-phase I/O algorithm, and explores using different data transfer primitives for the shuffle phase, including non-blocking two-sided communication and multiple versions of one-sided communication. The results indicate that overlap algorithms incorporating asynchronous I/O outperform overlapping approaches that only rely on non-blocking communication. However, in the vast majority of the testcases one-sided communication did not lead to performance improvements over two-sided communication.  more » « less
Award ID(s):
1663887
PAR ID:
10233062
Author(s) / Creator(s):
;
Date Published:
Journal Name:
2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)
Page Range / eLocation ID:
1 to 8
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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