We present AugeFS , a scalable userspace log-structured file system for modern SSDs. AugeFS re-architects the file system stack to address three critical challenges: inefficient control plane, limited metadata scalability, and underutilized device bandwidth. First, we propose a shared and protected address space within the userspace of accessing applications to run AugeFS , which enables the high-performance data plane and efficient control plane. Second, we design a scalable LSM-tree based key-value store called MetaDB to organize small-sized metadata in AugeFS . To improve the metadata scalability, MetaDB employs parallel request processing to reduce thread synchronization overhead and fine-grained parallel write-ahead log to eliminate false sharing in metadata persistence. Finally, AugeFS distributes files into different domains. To reduce contention, we maintain space management metadata for each domain independently, which helps scale data performance and improve the device IO utilization. Moreover, AugeFS designs an asynchronous IO stack for fsync to reduce the latency of synchronous writes. The evaluation results show that AugeFS significantly improves both metadata scalability and data scalability.

Memory-mapped IO offers several advantages over explicit read/write IO. It requires no system call, incurs minimal overhead in case of cache hits, and avoids extra data copies between user and kernel space. However, we still identify inefficiencies in current memory-mapped IO designs when meeting fast storage devices: i) the heavy IO stack in the page fault handler, ii) the suboptimal prefetching design, and iii) the inefficient eviction policy. To address these limitations, we present SuperMap, an alternative design for the memory-mapped IO in Linux, which specifically brings high performance and flexibility for fast devices. First, SuperMap designs a lightweight and asynchronous IO stack by directly accessing device, reducing software overhead significantly. Second, SuperMap introduces a fine-grained and application-customized prefetcher framework based on eBPF, further improving performance. Third, SuperMap proposes a hotness-aware eviction policy with the hardware assistance, trying to keep frequently accessed data in memory. Through evaluations using benchmarks and real-world applications, we demonstrate that SuperMap outperforms the state-of-the-art memory-mapped IO design (FastMap) up to 67%.

Persistent memory (PM) allows file systems to directly persist data on the memory bus. In order to expand the capacity of PM file system, building a file system across sockets with each attached PMs is attractive. However, accessing data across sockets incurs impacts of non-uniform memory access (NUMA) architecture, which degrade PM file system performance. In this paper, we first conduct experiments to understand the NUMA impacts on building PM file systems. We then propose four design principles for building a high-performance NUMA-aware PM file system NapFS. We architect NapFS with per-socket local PM file systems and per-socket dedicated IO thread pools. This not only allows applications to delegate data access to IO threads for avoiding remote PM access, but also fully reuses existing single-socket PM file systems to reduce implementation complexity. In addition, NapFS utilizes fast DRAM to accelerate performance by adding a global cache. We evaluate NapFS against other multi-socket PM file systems. The evaluation results show that NapFS achieves 2.2× and 1.0× throughput improvement for Filebench and RocksDB.