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A STUDY OF I/O IN A PARALLEL FINITE ELEMENT GROUNDWATER TRANSPORT CODE

机译:并行有限元地下水运输代码中I / O的研究

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摘要

A parallel finite element groundwater transport code is used to compare three different strategies for performing parallel I/O: (1) have a single processor collect data and perform sequential I/O in large blocks, (2) use variations of vendor-specific I/O extensions, or (3) use the extended distributed object network I/O (EDONIO) library. Each processor performs many writes of 1 to 4 kilobytes to reorganize local data in a global shared file. The findings suggest having a single processor collect data and perform large block-contiguous operations may be quite efficient and portable for up to 32 processor configurations. This approach does not scale well for a larger number of processors because the single processor becomes a bottleneck for gathering data. The effective application I/O rate observed, which includes times for opening and closing files, is only a fraction of the peak device read/write rates. Some form of data redistribution and buffering in remote memory as performed in EDONIO may yield significant improvements for noncontiguous data I/O access patterns and short requests. Implementors of parallel I/O systems may consider some form of buffering as performed in EDONIO to speed up such I/O requirements.
机译:并行有限元地下水传输代码用于比较执行并行I / O的三种不同策略:(1)使单个处理器收集数据并按大块执行顺序I / O;(2)使用供应商特定I的变体/ O扩展,或(3)使用扩展的分布式对象网络I / O(EDONIO)库。每个处理器执行1到4 KB的多次写操作,以重组全局共享文件中的本地数据。研究结果表明,使用单个处理器来收集数据并执行大块连续操作对于多达32个处理器配置而言可能非常高效且可移植。对于单个处理器,此方法无法很好地扩展,因为单个处理器成为收集数据的瓶颈。观察到的有效应用程序I / O速率(包括打开和关闭文件的时间)仅是峰值设备读/写速率的一小部分。在EDONIO中执行的某种形式的数据重新分配和在远程内存中缓冲可能会显着改善非连续数据I / O访问模式和短请求。并行I / O系统的实现者可以考虑在EDONIO中执行某种形式的缓冲,以加快此类I / O要求。

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