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MPI collective I/O is a widely used I/O method that helps data-intensive scientific applications gain better I/O performance. However, it has been observed that existing collective I/O strategies do not perform well due to the access contention problem. Existing collective I/O optimization strategies mainly focus on the I/O phase efficiency and ignore the shuffle cost that may limit the potential...
Data prefetching can be beneficial for improving parallel I/O system performance, but the amount of benefit depends on how efficiently and swiftly prefetches can be done. In this study, we propose a new prefetching strategy, called collective prefetching. The idea is to exploit the correlation among I/O accesses of multiple processes of a parallel application and carry out prefetches collectively,...
Parallel applications can benefit greatly from massive 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 parallel computing systems. In this study, we propose a data layout-aware optimization strategy to promote a better integration of the parallel I/O middleware...
Parallel I/O prefetching is considered to be effective in improving I/O performance. However, the effectiveness depends on determining patterns among future I/O accesses swiftly and fetching data in time, which is difficult to achieve in general. In this study, we propose an I/O signature-based prefetching strategy. The idea is to use a predetermined I/O signature of an application to guide prefetching...
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