Dynamic Data Race Detection for MPI-RMA Programs - Inria - Institut national de recherche en sciences et technologies du numérique
Communication Dans Un Congrès Année : 2021

Dynamic Data Race Detection for MPI-RMA Programs

Marc Sergent
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Emmanuelle Saillard
Denis Barthou
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Guillaume Papauré
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Résumé

One-sided communications is a well known distributed programming paradigm for high performance computers, as its properties allows for a greater asynchronism and computation/communication overlap than classical message passing mechanisms. In this paper, we focus on the Remote Memory Access interface of MPI (MPI-RMA), in which each process explicitly exposes an area of its local memory as accessible to other processes to provide asynchronous one-sided reads, writes and updates. While MPI-RMA is expected to greatly enhance the performance and permit efficient implementations on multiple platforms, it also comes with several challenges with respect to memory consistency. Developers must handle complex memory consistency models and complex programming semantics. This paper presents the RMA-Analyzer, a new tool that detects memory consistency errors (also known as data races) during MPI-RMA program executions. It collects relevant MPI-RMA operations and load/store accesses during execution and performs an on-the-fly analysis to stop the program in case of a consistency violation. We validate our method on a collection of codes containing errors and on two real applications. Our experiments show that the RMA-Analyzer is scalable when running on MPI one-sided applications with an overhead of 40% at best. CCS CONCEPTS • Software and its engineering → Consistency; Dynamic analysis; Distributed programming languages; Software testing and debugging.
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Dates et versions

hal-03374614 , version 1 (14-12-2021)

Identifiants

  • HAL Id : hal-03374614 , version 1

Citer

Tassadit Célia Aitkaci, Marc Sergent, Emmanuelle Saillard, Denis Barthou, Guillaume Papauré. Dynamic Data Race Detection for MPI-RMA Programs. EuroMPI 2021 - European MPI Users's Group Meeting, Sep 2021, Munich, Germany. ⟨hal-03374614⟩

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