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High-performance parallel computers require high-performance file systems. Exotic I/O hardware will be of little use if file system software runs on a single processor of a many-processor machine. We believe that cost-effective I/O for large multiprocessors can best be obtained by spreading both data and file system computation over a large number of processors and disks. To assess the effectiveness of this approach, we have implemented a prototype system called Bridge, and have studied its performance on several data intensive applications, among them external sorting. A detailed analysis of our sorting algorithm indicates that Bridge can profitably be used on configurations in excess of one hundred processors with disks. Empirical results on a 32-processor implementation agree with the analysis, providing us with a high degree of confidence in this prediction. Based on our experience, we argue that file systems such as Bridge will satisfy the I/O needs of a wide range of parallel architectures and applications.
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Dibble et al. (1989) studied this question.
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