Abstract
Programming models for task-based parallelization based on compile-time directives are very effective at uncovering the parallelism available in HPC applications. Despite that, the process of correctly annotating complex applications is error-prone and may hinder the general adoption of these models. In this paper, we target the OmpSs-2 programming model and present a novel toolchain able to detect parallelization errors coming from non-compliant OmpSs-2 applications. Our toolchain verifies the compliance with the OmpSs-2 programming model using local task analysis to deal with each task separately, and structural induction to extend the analysis to the whole program. To improve the effectiveness of our tools, we also introduce some ad-hoc verification annotations, which can be used manually or automatically to disable the analysis of specific code regions. Experiments run on a sample of representative kernels and applications show that our toolchain can be successfully used to verify the parallelization of complex real-world applications.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
For a thorough explanation of the admitted syntax for data references, see the official OmpSs-2 specification: https://pm.bsc.es/ftp/ompss-2/doc/spec/.
- 2.
Compared to the reference description in Sect. 2, our tools support additional OmpSs-2 features: commutative and concurrent dependencies (treated like inout), explicit release of dependencies, final and if clauses. Primitives for task reductions, atomic operations, and critical regions are currently unsupported. Additional information, included the instructions on how to install and use the toolchain, can be found here: https://github.com/bsc-pm/ompss-2-linter.
- 3.
Although our tool targets the AMD64 instruction set, this does not limit the scope of our work as it can be easily ported to other ISA and processor models.
- 4.
A comprehensive evaluation of the accuracy of our toolchain will be provided in a subsequent study.
References
AdaCore, Altran, Astrium Space Transportation, CEA-LIST, ProVal at INRIA and Thales Communications: Project Hi-Lite: GNATprove (2017). http://www.open-do.org/projects/hi-lite/gnatprove
Arb: OpenMP specification v5.0 (2018). https://www.openmp.org/wp-content/uploads/OpenMP-API-Specification-5.0.pdf
Atzeni, S., et al.: ARCHER: effectively spotting data races in large OpenMP applications. In: 2016 IEEE International Parallel and Distributed Processing Symposium (IPDPS), pp. 53–62 (2016)
Atzeni, S., Gopalakrishnan, G., Rakamaric, Z., Laguna, I., Lee, G.L., Ahn, D.H.: SWORD: a bounded memory-overhead detector of OpenMP data races in production runs. In: 2018 IEEE International Parallel and Distributed Processing Symposium (IPDPS), pp. 845–854 (2018)
Basupalli, V., et al.: ompVerify: polyhedral analysis for the OpenMP programmer. In: Chapman, B.M., Gropp, W.D., Kumaran, K., Müller, M.S. (eds.) IWOMP 2011. LNCS, vol. 6665, pp. 37–53. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-21487-5_4
Carpenter, P.M., Ramirez, A., Ayguade, E.: Starsscheck: a tool to find errors in task-based parallel programs. In: D’Ambra, P., Guarracino, M., Talia, D. (eds.) Euro-Par 2010. LNCS, vol. 6271, pp. 2–13. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-15277-1_2
Economo, S.: Techniques and tools for program tracing and analysis with applications to parallel programming. Ph.D. thesis, Sapienza Università di Roma (2020)
Economo, S., Royuela, S., Ayguadé, E., Beltran, V.: Artifact and instructions to generate experimental results for the conference proceeding 2020 paper: a Toolchain to Verify the Parallelization of OmpSs-2 Applications, July 2020. https://doi.org/10.6084/m9.figshare.12605180
Ferrer, R., Royuela, S., Caballero, D., Duran, A., Martorell, X., Ayguadé, E.: Mercurium: design decisions for a S2S compiler. In: Cetus Users and Compiler Infrastructure Workshop in Conjunction with PACT (2011)
Gu, Y., Mellor-Crummey, J.: Dynamic data race detection for OpenMP programs. In: Proceedings of the International Conference for High Performance Computing, Networking, Storage, and Analysis, SC 2018. IEEE Press (2018)
Jannesari, A., Bao, K., Pankratius, V., Tichy, W.F.: Helgrind+: an efficient dynamic race detector. In: 2009 IEEE International Symposium on Parallel Distributed Processing, pp. 1–13, May 2009
Lin, Y.: Static nonconcurrency analysis of OpenMP programs. In: Mueller, M.S., Chapman, B.M., de Supinski, B.R., Malony, A.D., Voss, M. (eds.) IWOMP -2005. LNCS, vol. 4315, pp. 36–50. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-68555-5_4
Luk, C.K., et al.: Pin: building customized program analysis tools with dynamic instrumentation. In: Proceedings of the 2005 ACM SIGPLAN Conference on Programming Language Design and Implementation, PLDI 2005, pp. 190–200. Association for Computing Machinery (2005)
Ma, H., Diersen, S.R., Wang, L., Liao, C., Quinlan, D., Yang, Z.: Symbolic analysis of concurrency errors in OpenMP programs. In: 2013 42nd International Conference on Parallel Processing, pp. 510–516 (2013)
Matar, H.S., Unat, D.: Runtime determinacy race detection for OpenMP tasks. In: Aldinucci, M., Padovani, L., Torquati, M. (eds.) Euro-Par 2018. LNCS, vol. 11014, pp. 31–45. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-96983-1_3
Perez, J.M., Beltran, V., Labarta, J., Ayguadé, E.: Improving the integration of task nesting and dependencies in OpenMP. In: 2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS), pp. 809–818 (2017)
Reinders, J.: Intel Threading Building Blocks - Outfitting C++ for Multi-Core Processor Parallelism. O’Reilly Media (2007)
Royuela, S., Ferrer, R., Caballero, D., Martorell, X.: Compiler analysis for OpenMP tasks correctness. In: Computing Frontiers. ACM (2015)
Serebryany, K., Iskhodzhanov, T.: ThreadSanitizer: data race detection in practice. In: Proceedings of the Workshop on Binary Instrumentation and Applications, WBIA 2009, pp. 62–71. Association for Computing Machinery (2009)
Acknowledgments and Data Availability Statement
This project is supported by the European Union’s Horizon 2021 research and innovation programme under grant agreement No 754304 (DEEP-EST), by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871669 (AMPERE) and the Project HPC-EUROPA3 (INFRAIA-2016-1-730897), by the Ministry of Economy of Spain through the Severo Ochoa Center of Excellence Program (SEV-2015-0493), by the Spanish Ministry of Science and Innovation (contract TIN2015-65316-P), and by the Generalitat de Catalunya (2017-SGR-1481).
The datasets and code generated during and/or analysed during the current study are available in the Figshare repository: https://doi.org/10.6084/m9.figshare.12605180 [8].
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Economo, S., Royuela, S., Ayguadé, E., Beltran, V. (2020). A Toolchain to Verify the Parallelization of OmpSs-2 Applications. In: Malawski, M., Rzadca, K. (eds) Euro-Par 2020: Parallel Processing. Euro-Par 2020. Lecture Notes in Computer Science(), vol 12247. Springer, Cham. https://doi.org/10.1007/978-3-030-57675-2_2
Download citation
DOI: https://doi.org/10.1007/978-3-030-57675-2_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-57674-5
Online ISBN: 978-3-030-57675-2
eBook Packages: Computer ScienceComputer Science (R0)