Erasure-coded archival converts the redundancy mechanism of low access-frequency data from replication to erasure coding for balancing access performance and storage efficiency. A variety of pipelined schemes are designed to speed up the archival operation, however they neglect such three factors as heterogeneous network, under-utilization of replica resources and tight coupling with underlying platforms which restrict or even negate the performance gains. In this paper, we propose Archpipe, a fast and flexible pipelined erasure-coded archival scheme. It exhibits three distinct features: 1) heterogeneous network awareness, for a single-pipelined construction, sufficient-bandwidth links are given high scheduling priority to avoid network congestion, while considering locality to reducing network transmissions; 2) parallel encoding, the unused replica resources are exploited to adaptively construct multiple pipelines for each stripe based on the single-pipelined algorithm, thereby enabling parity blocks to be encoded in parallel; 3) loose coupling, it does not rely on specific block placement policies and stripe construction algorithms. Experimental results indicate that, Archpipe can be seamlessly integrated with common distributed storage systems, and it improves the erasure-coded archival performance by 3.6 ∼ 4.7× and 1.3 ∼ 2.6× in on-disk and in-memory scenarios, respectively.

The first commercial Non-Volatile Memory (NVM) (i.e., Intel Optane DC Persistent Memory) exhibits limited parallelism, especially for write operations, which is generally neglected by existing NVM-aware file systems. Besides, the concurrent control of file systems also limits their scalability on high-performance NVMs under mainstream multi-core architectures. To effectively exploit full parallelism inherent in both NVMs and multi-core processors to enhance the overall performance, this paper proposes a novel scalable persistent memory file system, called SPMFS. SPMFS first partitions global metadata structures of the file system into per-core structures to distribute load and relieve contention. Second, SPMFS presents a fine-grained range lock to support concurrent accesses upon a file. Finally, SPMFS designs a dedicated I/O thread pool to offer optimal parallelism inherent in underlying NVM regardless of varying user-threads. We implement an SPMFS prototype and evaluate it under a variety of workloads generated by IOtest, Filebench, FIO, and production traces from Alibaba Pangu. The experiments show that SPMFS provides better scalability, and achieves up to 2.37 × write throughput improvement over state-of-the-art kernel NVM-aware file systems (Ext4-DAX, NOVA, and PMFS) and user-space file systems (Strata and Libnvmmio), without sacrificing the read performance.