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Distributed Task Execution: Opportunities, Challenges and Lessons Learnt from OmpSs-2@Cluster (Invited Talk)

Authors Paul Carpenter , Omar Shaaban , Juliette Fournis d'Albiat , Isabel Piedrahita

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Subject Classification

ACM Subject Classification
  • Computing methodologies → Parallel computing methodologies
  • Software and its engineering → Parallel programming languages
  • Software and its engineering → Distributed programming languages
  • Software and its engineering → Runtime environments
  • Computer systems organization → Distributed architectures
Keywords
  • Task-based programming
  • distributed-memory clusters
  • programming models
  • runtime systems
  • task scheduling
  • data dependency management
  • load balancing
  • asynchronous communication

Metrics

Abstract

This talk will present recent advances in extending OmpSs-2 to distributed-memory systems, highlighting three contributions and the associated challenges. OmpSs-2@Cluster employs a common address space and weak accesses to support concurrent task creation and dataflow execution across nodes. Achieving good performance and scalability on 16 to 32 nodes requires detailed performance analysis together with a set of optimizations and runtime techniques, which I will outline in the talk. Second, I will describe how task offloading, in combination with BSC’s Dynamic Load Balancing (DLB), enables OmpSs-2@Cluster to mitigate load imbalance in MPI + OmpSs-2 programs with minimal application changes. Third, I will explain how the runtime can exploit the iterative structure of certain task dependency graphs to precompute communications and execute iterative regions efficiently, yielding performance and scalability comparable to state-of-the-art asynchronous MPI+X. Together, these results indicate that distributed tasking can combine productivity, adaptability, and high performance in modern HPC applications.

Cite As Get BibTex

Paul Carpenter, Omar Shaaban, Juliette Fournis d'Albiat, and Isabel Piedrahita. Distributed Task Execution: Opportunities, Challenges and Lessons Learnt from OmpSs-2@Cluster (Invited Talk). In 17th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 15th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2026). Open Access Series in Informatics (OASIcs), Volume 141, pp. 1:1-1:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026) https://doi.org/10.4230/OASIcs.PARMA-DITAM.2026.1

Author Details

Paul Carpenter
  • Barcelona Supercomputing Center, Spain
Omar Shaaban
  • Barcelona Supercomputing Center, Spain
Juliette Fournis d'Albiat
  • Barcelona Supercomputing Center, Spain
Isabel Piedrahita
  • Barcelona Supercomputing Center, Spain

Funding

This work is funded by the Barcelona Zettascale Laboratory (REGAGE22e00058408992), backed by the Spanish Ministry for Digital Transformation and of Public Services, within the framework of the Recovery, Transformation, and Resilience Plan - funded by the European Union - NextGenerationEU. It is also supported by the Spanish State Research Agency - Ministry of Science and Innovation under contract PID2019-107255GB-C21/MCIN/AEI/10.13039/501100011033 and Ramon y Cajal fellowship RYC2018-025628-I/MCIN/AEI/10.13039/501100011033 and by "ESF Investing in your future", as well as by the Generalitat de Catalunya (2017-SGR-1414).

References

  1. Jimmy Aguilar Mena, Omar Shaaban, Vicenç Beltran, Paul Carpenter, Eduard Ayguadé, and Jesus Labarta. OmpSs-2@Cluster: Distributed memory execution of nested OpenMP-style tasks. In European Conference on Parallel Processing, 2022. URL: https://doi.org/10.1007/978-3-031-12597-3_20.
  2. Emmanuel Agullo, Olivier Aumage, Mathieu Faverge, Nathalie Furmento, Florent Pruvost, Marc Sergent, and Samuel Paul Thibault. Achieving high performance on supercomputers with a sequential task-based programming model. IEEE Transactions on Parallel and Distributed Systems, 2017. URL: https://doi.org/10.1109/TPDS.2017.2766064.
  3. David Álvarez and Vicenç Beltran. Optimizing iterative data-flow scientific applications using directed cyclic graphs. IEEE Access, 2023. URL: https://doi.org/10.1109/ACCESS.2023.3269902.
  4. Barcelona Supercomputing Center. OmpSs-2 specification, 2021. URL: https://pm.bsc.es/ftp/ompss-2/doc/spec/.
  5. Barcelona Supercomputing Center. OmpSs-2@Cluster releases, 2022. URL: https://github.com/bsc-pm/ompss-2-cluster-releases.
  6. Michael Bauer, Sean Treichler, Elliott Slaughter, and Alex Aiken. Legion: Expressing locality and independence with logical regions. In SC '12: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, 2012. URL: https://doi.org/10.1109/SC.2012.71.
  7. George Bosilca, Aurelien Bouteiller, Anthony Danalis, Thomas Herault, Pitior Luszczek, and Jack Dongarra. Dense linear algebra on distributed heterogeneous hardware with a symbolic DAG approach. Technical report, Lawrence Berkeley National Lab.(LBNL), Berkeley, CA (United States), 2012. URL: https://www.osti.gov/servlets/purl/1173290.
  8. J. Bueno, J. Planas, A. Duran, R. M. Badia, X. Martorell, E. Ayguadé, and J. Labarta. Productive programming of GPU clusters with OmpSs. In IEEE 26th International Parallel and Distributed Processing Symposium, 2012. URL: https://doi.org/10.1109/IPDPS.2012.58.
  9. Ewa Deelman, Gurmeet Singh, Mei-Hui Su, James Blythe, Yolanda Gil, Carl Kesselman, Gaurang Mehta, Karan Vahi, G. Berriman, John Good, Anastasia Laity, and Daniel S. Katz. Pegasus: A framework for mapping complex scientific workflows onto distributed systems. Scientific Programming, 13(3), 2005. URL: https://doi.org/10.1155/2005/128026.
  10. Alejandro Duran, Eduard Ayguadé, Rosa M Badia, Jesús Labarta, Luis Martinell, Xavier Martorell, and Judit Planas. OmpSs: a proposal for programming heterogeneous multi-core architectures. Parallel processing letters, 21(02), 2011. URL: https://doi.org/10.1142/S0129626411000151.
  11. Marta Garcia, Julita Corbalan, R.M Badia, and Jesus Labarta. A dynamic load balancing approach with SMPSuperscalar and MPI. Facing the Multicore - Challenge II. Lecture Notes in Computer Science, vol 7174, 2012. Google Scholar
  12. Reazul Hoque, Thomas Herault, George Bosilca, and Jack Dongarra. Dynamic task discovery in PaRSEC: a data-flow task-based runtime. In Proceedings of the 8th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, 2017. URL: https://doi.org/10.1145/3148226.3148233.
  13. Francesc Lordan, Enric Tejedor, Jorge Ejarque, Roger Rafanell, Javier Alvarez, Fabrizio Marozzo, Daniele Lezzi, Raül Sirvent, Domenico Talia, and Rosa M Badia. ServiceSs: An interoperable programming framework for the cloud. Journal of grid computing, 12(1), 2014. URL: https://doi.org/10.1007/s10723-013-9272-5.
  14. Jimmy Aguilar Mena. Methodology for malleable applications on distributed memory systems. PhD thesis, Universitat Politècnica de Catalunya, 2022. URL: https://doi.org/10.5821/dissertation-2117-380814.
  15. J. M. Perez, V. Beltran, J. Labarta, and E. Ayguadé. Improving the integration of task nesting and dependencies in OpenMP. In 2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2017. URL: https://doi.org/10.1109/IPDPS.2017.69.
  16. James Reinders. Intel Threading Building Blocks. O'Reilly & Associates, Inc., USA, 2007. Google Scholar
  17. Kevin Sala, Xavier Teruel, Josep M Perez, Antonio J Peña, Vicenç Beltran, and Jesus Labarta. Integrating blocking and non-blocking MPI primitives with task-based programming models. Parallel Computing, 2019. URL: https://doi.org/10.1016/j.parco.2018.12.008.
  18. Omar Shaaban Ibrahim ali, Juliette Fournis d'Albiat, Isabel Piedrahita, Vicenç Beltran, Xavier Martorell, Paul Carpenter, Eduard Ayguadé, and Jesus Labarta. Leveraging iterative applications to improve the scalability of task-based programming models on distributed systems. ACM Transactions on Architecture and Code Optimization, 22(3):1-27, 2025. URL: https://doi.org/10.1145/3743134.
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