Abstract
Heterogeneous systems have become a staple of the HPC environment. Several directive-based solutions, such as OpenMP and OpenACC, have been developed to alleviate the challenges of programming heterogeneous systems, and these standards strive to provide a single portable programming solution across heterogeneous environments. However, in many ways this goal has yet to be realized due to device-specific implementations and different levels of language support across compilers. In this framework we aim to analyze and address the different levels of optimization and compatibility between OpenACC and OpenMP programs and device compilers. We introduce the CCAMP framework, built on the OpenARC compiler, which implements language translation between OpenACC and OpenMP, with the goal of exploiting the maturity of different device-specific compilers to maximize performance for a given architecture. We show that CCAMP allows us to generate code for a specific device-compiler combination given a device-agnostic OpenMP or OpenACC program, allowing compilation and execution of programs with specific directives on otherwise incompatible devices. CCAMP also provides a starting point for a more advanced interoperable framework that can effectively provide directive translation and device, compiler, and application specific optimizations.
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.
The Power9+V100 configuration is very similar that of the Summit supercomputer nodes.
References
Arnold, G., Calvert, A., Overbey, J., Sultana, N.: From OpenACC to OpenMP 4: toward automatic translation. In: XCEDE 2016, Miami, FL (2016)
Bailey, D., Harris, T., Saphir, W., Van Der Wijngaart, R., Woo, A., Yarrow, M.: The NAS parallel benchmarks 2.0. Technical report, Technical Report NAS-95-020, NASA Ames Research Center (1995)
Dagum, L., Menon, R.: OpenMP: an industry-standard API for shared-memory programming. Comput. Sci. Eng. 1, 46–55 (1998)
Dave, C., Bae, H., Min, S.J., Lee, S., Eigenmann, R., Midkiff, S.: Cetus: a source-to-source compiler infrastructure for multicores. IEEE Comput. 42(12), 36–42 (2009). http://www.ecn.purdue.edu/ParaMount/publications/ieeecomputer-Cetus-09.pdf
Denny, J.E., Lee, S., Vetter, J.S.: CLACC: Translating OpenACC to OpenMP in clang. In: IEEE/ACM 5th Workshop on the LLVM Compiler Infrastructure in HPC (LLVM-HPC), pp. 18–29. IEEE (2018)
Gayatri, R., Yang, C., Kurth, T., Deslippe, J.: A case study for performance portability using OpenMP 4.5. In: Chandrasekaran, S., Juckeland, G., Wienke, S. (eds.) WACCPD 2018. LNCS, vol. 11381, pp. 75–95. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-12274-4_4
Juckeland, G., et al.: SPEC ACCEL: a standard application suite for measuring hardware accelerator performance. In: Jarvis, S.A., Wright, S.A., Hammond, S.D. (eds.) PMBS 2014. LNCS, vol. 8966, pp. 46–67. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-17248-4_3
Larrea, V.V., Joubert, W., Lopez, M.G., Hernandez, O.: Early experiences writing performance portable OpenMP 4 codes. In: Proceedings of the Cray User Group Meeting, London, England (2016)
Lee, S., Vetter, J.: OpenARC: open accelerator research compiler for directive-based, efficient heterogeneous computing. In: Proceedings of the ACM Symposium on High-Performance Parallel and Distributed Computing, HPDC 2014, Short Paper, June 2014
Lopez, M.G., et al.: Towards achieving performance portability using directives for accelerators. In: 2016 Third Workshop on Accelerator Programming Using Directives (WACCPD), pp. 13–24. IEEE (2016)
Mittal, S., Vetter, J.S.: A survey of CPU-GPU heterogeneous computing techniques. ACM Comput. Surv. (CSUR) 47(4), 69 (2015)
OpenACC: OpenACC: directives for accelerators (2011). http://www.openacc.org
Pino, S., Pollock, L., Chandrasekaran, S.: Exploring translation of OpenMP to OpenACC 2.5: lessons learned. In: IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), pp. 673–682. IEEE (2017)
Wolfe, M.: Compilers and more: OpenACC to OpenMP (and back again), June 2016. https://www.hpcwire.com/. Accessed 29 June 2016
Acknowledgements
This research was supported in part by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the U.S. Department of Energy Office of Science and the National Nuclear Security Administration.
This manuscript has been co-authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan.
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
Lambert, J., Lee, S., Malony, A., Vetter, J.S. (2020). CCAMP: OpenMP and OpenACC Interoperable Framework. In: Schwardmann, U., et al. Euro-Par 2019: Parallel Processing Workshops. Euro-Par 2019. Lecture Notes in Computer Science(), vol 11997. Springer, Cham. https://doi.org/10.1007/978-3-030-48340-1_28
Download citation
DOI: https://doi.org/10.1007/978-3-030-48340-1_28
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-48339-5
Online ISBN: 978-3-030-48340-1
eBook Packages: Computer ScienceComputer Science (R0)