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    Publications

    Publications by João Tiago Paulo

    2023

    Diagnosing applications' I/O behavior through system call observability

    Authors
    Esteves, T; Macedo, R; Oliveira, R; Paulo, J;

    Publication
    53rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2023 - Workshops, Porto, Portugal, June 27-30, 2023

    Abstract

    2021

    S2Dedup: SGX-enabled Secure Deduplication

    Authors
    Esteves, T; Miranda, M; Paulo, J; Portela, B;

    Publication
    IACR Cryptol. ePrint Arch.

    Abstract

    2021

    Soteria: Privacy-Preserving Machine Learning for Apache Spark

    Authors
    Brito, C; Ferreira, P; Portela, B; Oliveira, R; Paulo, J;

    Publication
    IACR Cryptol. ePrint Arch.

    Abstract

    2023

    Taming Metadata-intensive HPC Jobs Through Dynamic, Application-agnostic QoS Control

    Authors
    Macedo, R; Miranda, M; Tanimura, Y; Haga, J; Ruhela, A; Harrell, SL; Evans, RT; Pereira, J; Paulo, J;

    Publication
    2023 IEEE/ACM 23RD INTERNATIONAL SYMPOSIUM ON CLUSTER, CLOUD AND INTERNET COMPUTING, CCGRID

    Abstract
    Modern I/O applications that run on HPC infrastructures are increasingly becoming read and metadata intensive. However, having multiple applications submitting large amounts of metadata operations can easily saturate the shared parallel file system's metadata resources, leading to overall performance degradation and I/O unfairness. We present PADLL, an application and file system agnostic storage middleware that enables QoS control of data and metadata workflows in HPC storage systems. It adopts ideas from Software-Defined Storage, building data plane stages that mediate and rate limit POSIX requests submitted to the shared file system, and a control plane that holistically coordinates how all I/O workflows are handled. We demonstrate its performance and feasibility under multiple QoS policies using synthetic benchmarks, real-world applications, and traces collected from a production file system. Results show that PADLL can enforce complex storage QoS policies over concurrent metadata-aggressive jobs, ensuring fairness and prioritization.

    CloseRead Abstract

    2021

    PAIO: A Software-Defined Storage Data Plane Framework

    Authors
    Macedo, R; Tanimura, Y; Haga, J; Chidambaram, V; Pereira, J; Paulo, J;

    Publication
    CoRR

    Abstract

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