Skip to main content
SpringerLink
Log in

A Proposal for Loop-Transformation Pragmas

  • Conference paper
  • First Online:
Evolving OpenMP for Evolving Architectures (IWOMP 2018)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 11128))

Included in the following conference series:

Abstract

Pragmas for loop transformations, such as unrolling, are implemented in most mainstream compilers. They are used by application programmers because of their ease of use compared to directly modifying the source code of the relevant loops. We propose additional pragmas for common loop transformations that go far beyond the transformations today’s compilers provide and should make most source rewriting for the sake of loop optimization unnecessary. To encourage compilers to implement these pragmas, and to avoid a diversity of incompatible syntaxes, we would like to spark a discussion about an inclusion to the OpenMP standard.

The U.S. government retains certain licensing rights. This is a U.S. government work and certain licensing rights apply

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Bagnères, L., Zinenko, O., Huot, S., Bastoul, C.: Opening polyhedral compiler’s black box. In: 14th Annual IEEE/ACM International Symposium on Code Generation and Optimization (CGO 2016). IEEE (2016)

    Google Scholar 

  2. Attributes in Clang. http://clang.llvm.org/docs/AttributeReference.html

  3. Auto-Vectorization in LLVM. http://llvm.org/docs/Vectorizers.html

  4. Clang Language Extensions. http://clang.llvm.org/docs/LanguageExtensions.html

  5. Doerfert, J.: [RFC] abstract parallel IR optimizations. llvm-dev mailing list post, June 2018. http://lists.llvm.org/pipermail/llvm-dev/2018-June/123841.html

  6. Dolbeau, R., Bihan, S., Bodin, F.: HMPP™: a hybrid multi-core parallel programming environment. In: First Workshop on General Purpose Processing on Graphics Processing Units (GPGPU 2007) (2007)

    Google Scholar 

  7. Donadio, S., et al.: A language for the compact representation of multiple program versions. In: Ayguadé, E., Baumgartner, G., Ramanujam, J., Sadayappan, P. (eds.) LCPC 2005. LNCS, vol. 4339, pp. 136–151. Springer, Heidelberg (2006). https://doi.org/10.1007/978-3-540-69330-7_10

    Chapter  Google Scholar 

  8. Edwards, H.C., Trott, C.R., Sunderland, D.: Kokkos: enabling manycore performance portability through polymorphic memory access patterns. J. Parallel Distrib. Comput. 74(12), 3202–3216 (2014)

    Article  Google Scholar 

  9. Finkel, H., Doerfert, J., Tian, X., Stelle, G.: A parallel IR in real life: optimizing OpenMP. EuroLLVM 2018 presentation (2018). http://llvm.org/devmtg/2018-04/talks.html#Talk_1

  10. Finkel, H., Tian, X.: [RFC] IR-level region annotations. llvm-dev mailing list post, January 2017. http://lists.llvm.org/pipermail/llvm-dev/2017-January/108906.html

  11. Free Software Foundation: Loop-Specific Pragmas. https://gcc.gnu.org/onlinedocs/gcc/Loop-Specific-Pragmas.html

  12. Girbal, S., et al.: Semi-automatic composition of loop transformations for deep parallelism and memory hierarchies. Int. J. Parallel Program. 34(3), 261–317 (2006)

    Article  Google Scholar 

  13. Grosser, T., Zheng, H., Aloor, R., Simbürger, A., Größlinger, A., Pouchet, L.N.: Polly - polyhedral optimization in LLVM. In: First International Workshop on Polyhedral Compilation Techniques (IMPACT 2011) (2011)

    Google Scholar 

  14. Hartono, A., Norris, B., Sadayappan, P.: Annotation-based empirical performance tuning using Orio. In: Proceedings of the 23rd IEEE International Parallel and Distributed Computing Symposium (IPDPS 2009). IEEE (2009)

    Google Scholar 

  15. Hornung, R.D., Keasler, J.A.: The RAJA portability layer: overview and status. Technical report LLNL-TR-661403, Lawrence Livermore National Lab (2014)

    Google Scholar 

  16. IBM: Product documentation for XL C/C++ for AIX, V13.1.3

    Google Scholar 

  17. Intel: Threading Building Blocks. https://www.threadingbuildingblocks.org

  18. Intel: Intel C++ Compiler 18.0 Developer Guide and Reference, May 2018

    Google Scholar 

  19. International Organization for Standardization: ISO/IEC 14882:2017, December 2017

    Google Scholar 

  20. Kelly, W., Pugh, W.: A framework for unifying reordering transformations. Technical report UMIACS-TR-93-134/CS-TR-3193, University of Maryland (1992)

    Google Scholar 

  21. Low, T.M., Igual, F.D., Smith, T.M., Quintana-Orti, E.S.: Analytical modeling is enough for high-performance BLIS. Trans. Math. Softw. (TOMS) 43(2), 12:1–12:18 (2016)

    MathSciNet  MATH  Google Scholar 

  22. Microsoft: C/C++ Preprocessor Reference. http://docs.microsoft.com/en-us/cpp/preprocessor/loop

  23. Müller-Pfefferkorn, R., Nagel, W.E., Trenkler, B.: Optimizing cache access: a tool for source-to-source transformations and real-life compiler tests. In: Danelutto, M., Vanneschi, M., Laforenza, D. (eds.) Euro-Par 2004. LNCS, vol. 3149, pp. 72–81. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-27866-5_10

    Chapter  Google Scholar 

  24. OpenACC-Standard.org: The OpenACC Application Programming Interface Version 4.0, November 2017

    Google Scholar 

  25. OpenMP Architecture Review Board: OpenMP Application Program Interface Version 4.0, July 2017

    Google Scholar 

  26. Ragan-Kelley, J., Barnes, C., Adams, A., Paris, S., Durand, F., Amarasinghe, S.: Halide: a language and compiler for optimizing parallelism, locality, and recomputation in image processing pipelines. In: Proceedings of the 34th ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI 2013), pp. 519–530. ACM (2013)

    Google Scholar 

  27. Saito, H.: Extending LoopVectorizer towards supporting OpenMP4.5 SIMD and outer loop auto-vectorization. EuroLLVM 2018 presentation (2016). http://llvm.org/devmtg/2016-11/#talk7

  28. Schardl, T.B., Moses, W.S., Leiserson, C.E.: Tapir: embedding fork-join parallelism into LLVM’s intermediate representation. In: Proceedings of the 22nd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP 2017), pp. 249–265. ACM (2017)

    Google Scholar 

  29. Tian, X., et al.: LLVM framework and IR extensions for parallelization, SIMD vectorization and offloading. In: Third Workshop on the LLVM Compiler Infrastructure in HPC (LLVM-HPC 2016). IEEE (2016)

    Google Scholar 

  30. Tiwari, A., Chen, C., Chame, J., Hall, M., Hollingsworth, J.K.: A scalable auto-tuning framework for compiler optimization. In: Proceedings of the 23rd IEEE International Parallel and Distributed Computing Symposium (IPDPS 2009). IEEE (2009)

    Google Scholar 

  31. Vasilache, N., et al.: Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions. CoRR abs/1802.04730 (2018)

    Google Scholar 

  32. Verdoolaege, S., Guelton, S., Grosser, T., Cohen, A.: Schedule trees. In: Fourth International Workshop on Polyhedral Compilation Techniques (IMPACT 2014) (2014)

    Google Scholar 

  33. Yi, Q., Seymour, K., You, H., Vuduc, R., Quinlan, D.: POET: parameterized optimizations for empirical tuning. In: Proceedings of the 21st IEEE International Parallel And Distributed Computing Symposium (IPDPS 2007). IEEE (2007)

    Google Scholar 

  34. Zinenko, O., Huot, S., Bastoul, C.: Clint: a direct manipulation tool for parallelizing compute-intensive program parts. In: 2014 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC). IEEE (2014)

    Google Scholar 

Download references

Acknowledgments

This research was supported by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of two U.S. Department of Energy organizations (Office of Science and the National Nuclear Security Administration) responsible for the planning and preparation of a capable exascale ecosystem, including software, applications, hardware, advanced system engineering, and early testbed platforms, in support of the nations exascale computing imperative.

This research used resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357.

Author information

Authors and Affiliations

  1. Argonne Leadership Computing Facility, Argonne National Laboratory, Argonne, IL, 60439, USA

    Michael Kruse & Hal Finkel

Authors
  1. Michael Kruse
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hal Finkel
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Michael Kruse .

Editor information

Editors and Affiliations

  1. Lawrence Livermore National Laboratory, Livermore, CA, USA

    Bronis R. de Supinski

  2. Barcelona Supercomputing Center, Barcelona, Barcelona, Spain

    Pedro Valero-Lara

  3. Universitat Politècnica de Catalunya, Barcelona, Spain

    Xavier Martorell

  4. Barcelona Supercomputing Center, Barcelona, Barcelona, Spain

    Sergi Mateo Bellido

  5. Universitat Politècnica de Catalunya, Barcelona, Barcelona, Spain

    Jesus Labarta

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Kruse, M., Finkel, H. (2018). A Proposal for Loop-Transformation Pragmas. In: de Supinski, B., Valero-Lara, P., Martorell, X., Mateo Bellido, S., Labarta, J. (eds) Evolving OpenMP for Evolving Architectures. IWOMP 2018. Lecture Notes in Computer Science(), vol 11128. Springer, Cham. https://doi.org/10.1007/978-3-319-98521-3_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-98521-3_3

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-98520-6

  • Online ISBN: 978-3-319-98521-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation