Dynamically adaptable i/o semantics for high performance computing

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Abstract

While an input/output (I/O) interface’s syntax describes the available operations, its semantics determines how these operations behave and which assumptions developers can make about them. There are several different interface standards in existence, some of them dating back decades and having been designed for local file systems; one such representative is POSIX. Many parallel distributed file systems implement a POSIX-compliant interface to improve portability. All currently available interfaces follow a fixed approach regarding semantics, making them only suitable for a subset of use cases and workloads. While the interfaces do not allow application developers to influence the I/O semantics, applications could benefit greatly from the possibility of being able to adapt them to their requirements. The work presented in this paper includes the design of a novel I/O interface and a file system called JULEA. They offer support for dynamically adaptable semantics and are suited specifically for HPC applications. The introduced concept allows applications to adapt the file system behavior to their exact I/O requirements instead of the other way around. The general goal is an interface that allows developers to specify what operations should do and how they should behave – leaving the actual realization and possible optimizations to the underlying file system. JULEA has been evaluated using both synthetic benchmarks and real-world applications. Overall, JULEA provides data and metadata performance comparable to that of other established parallel distributed file systems. However, in contrast to the existing solutions, its flexible semantics allows it to cover a wider range of use cases in an efficient way. The results demonstrate that there is need for I/O interfaces that can adapt to the requirements of applications. Even though POSIX facilitates portability, it does not seem to be suited for contemporary HPC demands.

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APA

Kuhn, M. (2015). Dynamically adaptable i/o semantics for high performance computing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9137 LNCS, pp. 240–256). Springer Verlag. https://doi.org/10.1007/978-3-319-20119-1_18

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