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DAOS as HPC Storage, a view from Numerical Weather Prediction

2022/08/14 by Nicolau Manubens, Manubens, Nicolau, Tiago Quintino +6 · 1 citation
Computer Science · #Advanced Data Storage Technologies #Distributed #Distributed and Parallel Computing Systems #FOS: Computer and information sciences #Parallel #Parallel Computing and Optimization Techniques #and Cluster Computing (cs.DC)

paper · pdf · doi:10.48550/arxiv.2208.06752

openalex publication_date 2022/08/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/04

Abstract

Object storage solutions potentially address long-standing performance issues with POSIX file systems for certain I/O workloads, and new storage technologies offer promising performance characteristics for data-intensive use cases. In this work, we present a preliminary assessment of Intel's Distributed Asynchronous Object Store (DAOS), an emerging high-performance object store, in conjunction with non-volatile storage and evaluate its potential use for HPC storage. We demonstrate DAOS can provide the required performance, with bandwidth scaling linearly with additional DAOS server nodes in most cases, although choices in configuration and application design can impact achievable bandwidth. We describe a new I/O benchmark and associated metrics that address object storage performance from application-derived workloads.

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