Improving Parallel I/O Performance with Data Layout Awareness
Authors: Y. Chen, X.-H. Sun, R. Thakur, H. Song, H. Jin
Date: September, 2010
Venue: The IEEE International Conference on Cluster Computing 2010 (Cluster10), Heraklion, Greece
Type: Conference
Abstract
Parallel applications can benefit greatly from mas- sive computational capability, but their performance suffers from large latency of I/O accesses. The poor I/O performance has been attributed as a critical cause of the low sustained performance of paral- lel computing systems. In this study, we propose a data layout-aware optimization strategy to promote a better integration of the parallel I/O middleware and parallel file systems, two major components of the current parallel I/O systems, and to improve the data access performance. We explore the layout-aware optimization in both independent I/O and collective I/O, two primary forms of I/O in parallel applications. We illustrate that the layout-aware I/O optimization could improve the performance of current parallel I/O strategy effectively. The experimental results verify that the proposed strategy could improve parallel I/O performance by nearly 40% on average. The proposed layout-aware parallel I/O has a promising potential in improving the I/O performance of parallel systems.