Rethinking File Mapping for Persistent Memory
Rethinking File Mapping for Persistent Memory
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发表时间：
2021
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通讯作者：
Ian Neal;Gefei Zuo;Eric Shiple;Tanvir Ahmed Khan;Youngjin Kwon;Simon Peter;Baris Kasikci
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作者：
Ian Neal;Gefei Zuo;Eric Shiple;Tanvir Ahmed Khan;Youngjin Kwon;Simon Peter;Baris Kasikci
永久性主内存（PM）显著提高了IO性能。我们发现，这会导致PM上的文件系统花费多达70%的IO路径在真实的工作负载上执行文件映射（将文件偏移映射到存储介质上的物理位置）。然而，即使是PM优化的文件系统也是基于几十年前的假设来执行文件映射的。现在，重新访问PM的文件映射至关重要。我们探索PM文件映射的设计空间，通过构建和评估几个文件映射设计，包括不同的数据结构，缓存，以及元数据和块分配方法，在PM优化的文件系统的上下文中。基于我们的研究结果，我们设计了HashFS，一个基于散列的文件映射方法。HashFS对所有映射和分配操作使用单个散列操作，绕过文件系统缓存，而是通过SIMD并行预取映射并显式缓存转换。HashFS由此产生的低延迟提供了比替代方案更优越的上级性能。HashFS将LevelDB上YCSB的吞吐量提高了45%，超过了最先进的Strata PM优化文件系统中的页面缓存扩展树。
Persistent main memory (PM) dramatically improves IO performance. We find that this results in file systems on PM spending as much as 70% of the IO path performing file mapping (mapping file offsets to physical locations on storage media) on real workloads. However, even PM-optimized file systems perform file mapping based on decades-old assumptions. It is now critical to revisit file mapping for PM. We explore the design space for PM file mapping by building and evaluating several file-mapping designs, including different data structure, caching, as well as meta-data and block allocation approaches, within the context of a PM-optimized file system. Based on our findings, we design HashFS, a hashbased file mapping approach. HashFS uses a single hash operation for all mapping and allocation operations, bypassing the file system cache, instead prefetching mappings via SIMD parallelism and caching translations explicitly. HashFS’s resulting low latency provides superior performance compared to alternatives. HashFS increases the throughput of YCSB on LevelDB by up to 45% over page-cached extent trees in the state-of-the-art Strata PM-optimized file system.