ABR: CSR: Medium: Collaborative Research: FTFS: A Read/Write Optimized Fractal Tree File System

计算机应用程序依赖文件系统来安全高效地读取、写入和访问用户数据。不幸的是，传统的文件系统设计以牺牲其他应用程序为代价来提高某些应用程序的速度；类似地，大多数文件系统被设计为在一种特定类型的存储设备上运行良好，例如硬盘驱动器(HDD)或基于闪存的固态驱动器(SSD)。目前，各种各样的终端用户没有充分发挥其存储硬件的性能潜力，除非他们能够选择与其特定工作负载和硬件非常匹配的文件系统。之前关于BetrFS文件系统原型的工作表明，使用更好的磁盘数据结构，可以构建一个大致匹配或超过HDD上任何工作负载的最佳文件系统性能的单个文件系统。该项目将通过系统和理论研究人员之间紧密的跨学科合作，将这些性能提升扩展到更广泛的存储硬件，从复杂的归档设备(如瓦式磁记录驱动器)到非常快的闪存设备(如非易失性快速存储器设备)。该项目还将研究一种更有效的目录级克隆方法，这是服务器工作负载和个人计算系统的有用构件。通过使大量应用程序在一系列存储硬件上更快地运行，该项目可以在现实中带来显著的好处。存储硬件正变得越来越多样化，该项目可以帮助任何应用程序的性能经得起未来考验，从商业到医疗保健，再到科学计算到教育。该项目涉及将这些想法从研究转化为实践的重要组成部分，包括完善开放源码BetrFS原型，以及为实践者提供持续的外联和教程。该项目将继续培训本科生和研究生设计、分析、构建和测量算法健全的计算机系统，这些系统是他们以前见过的任何不同的系统。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Computer applications rely on file systems to read, write, and access user data safely and efficiently. Unfortunately, conventional file system designs make some applications fast at the expense of others; similarly, most file systems are designed to perform well on one particular type of storage device, such as a hard disk drive (HDD) or flash-based solid-state drive (SSD). Currently, a wide variety of end-users do not realize the full performance potential of their storage hardware, unless they are able to select a file system that is well-matched to their specific workload and hardware. Prior work on the BetrFS file system prototype demonstrated that, with better on-disk data structures, it is possible to build a single file system that roughly matches or exceeds the performance of the best file system for any workload on an HDD. This project will extend these performance gains, which are enabled by a tight, cross-disciplinary collaboration between systems and theory researchers, to a wider range of storage hardware, ranging from complex, archival devices (such as shingled magnetic recording drives), to very fast flash devices (such as non-volatile memory express devices). This project will also investigate a more efficient approach to directory-level cloning, a useful building block for both server workloads and personal computing systems. By making a large swath of applications run faster across a range of storage hardware, this project can have significant real-world benefits. Storage hardware is becoming increasingly varied, and this project can help future-proof the performance of any application, from commerce to health-care to scientific computing to education. This project involves an important component to transition these ideas from research to practice, including maturing the open-source BetrFS prototype, as well as continuing outreach and tutorials for practitioners. This project will continue training both undergraduate and graduate students to design, analyze, build, and measure algorithmically sound computer systems that are unlike anything they have seen previously.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.