Server-directed collective I/O in Panda
Supercomputing '95 Proceedings of the 1995 ACM/IEEE conference on Supercomputing
Persistent Array Access Using Server-Directed I/O
SSDBM '96 Proceedings of the Eighth International Conference on Scientific and Statistical Database Management
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As parallel computers are increasingly used to run scientific applications with large data sets, and as processor speeds continue to increase, it becomes more important to provide fast, effective parallel file systems for data storage and for temporary files. In an earlier work we demonstrated that a technique we call disk-directed I/O has the potential to provide consistent high performance for large, collective, structured I/O requests. In this paper we expand on this potential by demonstrating the ability of a disk-directed I/O system to read irregular subsets of data from a file, and to filter and distribute incoming data according to data-dependent functions.