Rethinking Data Race Detection in MPI-RMA Programs - Inria - Institut national de recherche en sciences et technologies du numérique
Communication Dans Un Congrès Année : 2023

Rethinking Data Race Detection in MPI-RMA Programs

Van Man Nguyen
  • Fonction : Auteur
  • PersonId : 1303811
Marc Sergent
Emmanuelle Saillard

Résumé

Supercomputers are capable of increasingly more computations, and nodes forming them need to communicate even more efficiently with each other. The Message Passing Interface (MPI) proposes a communication model based on one-sided communications called the MPI Remote Memory Access (MPI-RMA). Thanks to these operations, applications can improve the overlap of communications with computations. However, one-sided communications are complex to write since they are subject to data races. This paper rethinks an existing on-the-fly data race detection algorithm for MPI-RMA programs by improving the storage of memory accesses in a Binary Search Tree using a new insertion algorithm based on fragmentation and merging algorithms. Thus, experimental results on real-life applications show that this new insertion algorithm improves the accuracy of the data race detection and can reduce the overhead of the analysis at runtime by a factor up to two.
Fichier principal
Vignette du fichier
MPI-RMA-races.pdf (900.76 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04272399 , version 1 (06-11-2023)

Identifiants

Citer

Radjasouria Vinayagame, Van Man Nguyen, Marc Sergent, Samuel Thibault, Emmanuelle Saillard. Rethinking Data Race Detection in MPI-RMA Programs. 7th International Workshop on Software Correctness for HPC Applications (Correctness '23), Nov 2023, Denver (Colorado, USA), United States. pp.196-204, ⟨10.1145/3624062.3624086⟩. ⟨hal-04272399⟩

Collections

CNRS INRIA INRIA2
112 Consultations
95 Téléchargements

Altmetric

Partager

More