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- W2097976259 abstract "Efficient execution of parallel scientific applications requires high-performance storage systems designed to meet their I/O requirements. Most high-performance I/O intensive applications access multiple layers of the storage stack during their disk operations. A typical I/O request from these applications may include accesses to high-level libraries such as MPI I/O, executing on clustered parallel file systems like PVFS2, which are in turn supported by native file systems like Linux. In order to design and implement parallel applications that exercise this I/O stack, it is important to understand the flow of I/O calls through the entire storage system. Such understanding helps in identifying the potential performance and power bottlenecks in different layers of the storage hierarchy. To trace the execution of the I/O calls and to understand the complex interactions of multiple user-libraries and file systems, we propose an automatic code instrumentation technique, which enables us to collect detailed statistics of the I/O stack. Our proposed I/O tracing tool traces the flow of I/O calls across different layers of an I/O stack, and can be configured to work with different file systems and user-libraries. It also analyzes the collected information to generate output in terms of different user-specified metrics of interest." @default.
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- W2097976259 date "2010-01-01" @default.
- W2097976259 modified "2023-10-03" @default.
- W2097976259 title "Automated Tracing of I/O Stack" @default.
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- W2097976259 doi "https://doi.org/10.1007/978-3-642-15646-5_8" @default.
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