With the advent of new computing paradigms, parallel file systems serve not only traditional scientific computing applications but also non-scientific computing applications, such as financial computing, business, and public administration. Parallel file systems provide storage services for multiple applications. As a result, various requirements need to be met. However, parallel file systems usually provide a unified storage solution, which cannot meet specific application needs. In this paper, an extended file handle scheme is proposed to deal with this problem. The original file handle is extended to record I/O optimization information, which allows file systems to specify optimizations for a file or directory based on workload characteristics. Therefore, fine-grained management of I/O optimizations can be achieved. On the basis of the extended file handle scheme, data prefetching and small file optimization mechanisms are proposed for parallel file systems. The experimental results show that the proposed approach improves the aggregate throughput of the overall system by up to 189.75%.

随着新的计算范例的出现，并行文件系统不仅为传统的科学计算应用程序服务，而且还为非科学计算应用程序服务，例如金融计算，业务和公共管理。并行文件系统为多个应用程序提供存储服务。结果，需要满足各种要求。但是，并行文件系统通常提供统一的存储解决方案，无法满足特定的应用程序需求。本文提出了一种扩展的文件处理方案来解决这个问题。原始文件句柄被扩展为记录I / O优化信息，从而允许文件系统基于工作负载特征为文件或目录指定优化。因此，可以实现I / O优化的细粒度管理。在扩展文件处理方案的基础上，针对并行文件系统提出了数据预取和小文件优化机制。实验结果表明，所提出的方法将整个系统的总吞吐量提高了189.75％。