Lune

FAST2023Top-tier venue

HadaFS: A File System Bridging the Local and Shared Burst Buffer for Exascale Supercomputers

Xiaobin He, Bin Yang, Jie Gao, Wei Xiao, Qi Chen, Shupeng Shi, Dexun Chen, Weiguo Liu, Wei Xue, Zuoning Chen

2023Year
24Citations
1Top-tier citations

Abstract

Current supercomputers introduce SSDs to form a Burst Buffer (BB) layer to meet the HPC application's growing I/O requirements. BBs can be divided into two types by deployment location. One is the local BB, which is known for its scalability and performance. The other is the shared BB, which has the advantage of data sharing and deployment costs. How to unify the advantages of the local BB and the shared BB is a key issue in the HPC community.

We propose a novel BB file system named HadaFS that provides the advantages of local BB deployments to shared BB deployments. First, HadaFS offers a new Localized Triage Architecture (LTA) to solve the problem of ultra-scale expansion and data sharing. Then, HadaFS proposes a full-path indexing approach with three metadata synchronization strategies to solve the problem of complex metadata management of traditional file systems and mismatch with the application I/O behaviors. Moreover, HadaFS integrates a data management tool named Hadash, which supports efficient data query in the BB and accelerates data migration between the BB and traditional HPC storage. HadaFS has been deployed on the Sunway New-generation Supercomputer (SNS), serving hundreds of applications and supporting a maximum of 600,000-client scaling.

Ask about this paper

Your agent reads all of it.

Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.

Questions to start from

Your agent calls

Luneget_paper_fulltext

Ask in Lune

Free to start. No credit card required.

lune papers fulltext 85a4f130-d2e1-42d8-8be5-32af1952e9e7

Cited by top-tier papers1

Ask how each one uses it

Builds on2

Related papers

Dusk over the sea between two cliffs drawn in fine vertical lines