DeltaFS: a scalable no-ground-truth filesystem for massively-parallel computing
Qing Zheng, Charles D. Cranor, Gregory R. Ganger, Garth A. Gibson, George Amvrosiadis, Bradley W. Settlemyer, Gary A. Grider
摘要
High-Performance Computing (HPC) is known for its use of massive concurrency. But it can be challenging for a parallel filesystem's control plane to utilize cores when every client process must globally synchronize and serialize its metadata mutations with those of other clients. We present DeltaFS, a new paradigm for distributed filesystem metadata.
DeltaFS allows jobs to self-commit their namespace changes to logs, avoiding the cost of global synchronization. Followup jobs selectively merge logs produced by previous jobs as needed, a principle we term No Ground Truth which allows for efficient data sharing. By avoiding unnecessary synchronization of metadata operations, DeltaFS improves metadata operation throughput up to 98× leveraging parallelism on the nodes where job processes run. This speedup grows as job size increases. DeltaFS enables efficient inter-job communication, reducing overall workflow runtime by significantly improving client metadata operation latency up to 49× and resource usage up to 52×.
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- FalconFS: Distributed File System for Large-Scale Deep Learning PipelineJingwei Xu, Junbin Kang, Mingkai Dong, Mingyu Liu 等NSDI 2026 · 被引用 2 次
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