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High-Performance Defunctionalisation in Futhark

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Trends in Functional Programming (TFP 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11457))

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Abstract

General-purpose massively parallel processors, such as GPUs, have become common, but are difficult to program. Pure functional programming can be a solution, as it guarantees referential transparency, and provides useful combinators for expressing data-parallel computations. Unfortunately, higher-order functions cannot be efficiently implemented on GPUs by the usual means. In this paper, we present a defunctionalisation transformation that relies on type-based restrictions on the use of expressions of functional type, such that we can completely eliminate higher-order functions in all cases, without introducing any branching. We prove the correctness of the transformation and discuss its implementation in Futhark, a data-parallel functional language that generates GPU code. The use of these restricted higher-order functions has no impact on run-time performance, and we argue that we gain many of the benefits of general higher-order functions, without in most practical cases being hindered by the restrictions.

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Notes

  1. 1.

    In the actual implementation, the target language does include application of first-order functions, but in our theoretical work we just inline the functions for simplicity.

References

  1. Andreetta, C., et al.: FinPar: a parallel financial benchmark. ACM Trans. Arch. Code Optim. (TACO) 13(2), 18:1–18:27 (2016)

    Google Scholar 

  2. Annenkov, D.: Adventures in formalisation: financial contracts, modules, and two-level type theory. Ph.D. thesis, University of Copenhagen, April 2018

    Google Scholar 

  3. Blelloch, G.E.: Programming parallel algorithms. Commun. ACM (CACM) 39(3), 85–97 (1996)

    Article  Google Scholar 

  4. Chakravarty, M.M., Keller, G., Lee, S., McDonell, T.L., Grover, V.: Accelerating Haskell array codes with multicore GPUs. In: Workshop on Declarative Aspects of Multicore Programming, DAMP 2011. ACM, January 2011

    Google Scholar 

  5. Chakravarty, M.M., Leshchinskiy, R., Jones, S.P., Keller, G., Marlow, S.: Data parallel Haskell: a status report. In: Workshop on Declarative Aspects of Multicore Programming, DAMP 2007. ACM, January 2007

    Google Scholar 

  6. Charguéraud, A.: Pretty-big-step semantics. In: Felleisen, M., Gardner, P. (eds.) ESOP 2013. LNCS, vol. 7792, pp. 41–60. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-37036-6_3

    Chapter  Google Scholar 

  7. Che, S., et al.: Rodinia: a benchmark suite for heterogeneous computing. In: IEEE International Symposium on Workload Characterization, IISWC 2009, October 2009

    Google Scholar 

  8. Claessen, K., Sheeran, M., Svensson, B.J.: Expressive array constructs in an embedded GPU kernel programming language. In: Workshop on Declarative Aspects of Multicore Programming, DAMP 2012. ACM, January 2012

    Google Scholar 

  9. Elliott, C.: Functional images. In: The Fun of Programming. Cornerstones of Computing Series. Palgrave, March 2003

    Chapter  Google Scholar 

  10. Elliott, C., Finne, S., de Moor, O.: Compiling embedded languages. J. Funct. Program. 13(2), 455–481 (2003)

    Article  Google Scholar 

  11. Elsman, M.: Polymorphic equality–no tags required. In: Second International Workshop on Types in Compilation (TIC 1998), March 1998

    Google Scholar 

  12. Elsman, M.: Static interpretation of modules. In: Proceedings of the ACM SIGPLAN International Conference on Functional Programming, ICFP 1999. ACM Press, September 1999

    Google Scholar 

  13. Elsman, M.: Type-specialized serialization with sharing. In: Sixth Symposium on Trends in Functional Programming (TFP 2005), September 2005

    Google Scholar 

  14. Elsman, M., Henriksen, T., Annenkov, D., Oancea, C.E.: Static interpretation of higher-order modules in Futhark: functional GPU programming in the large. Proc. ACM Program. Lang. 2(ICFP), 97:1–97:30 (2018)

    Article  Google Scholar 

  15. Elsman, M., Henriksen, T., Oancea, C.E.: Parallel Programming in Futhark. Department of Computer Science, University of Copenhagen, November 2018. https://futhark-book.readthedocs.io

  16. Girard, J.Y.: Interpretation Fonctionnelle et Elimination des Coupures de l’Arithmetique d’Ordre Superieur. In: Proceedings of the Second Scandinavian Logic Symposium, pp. 63–92. North-Holland (1971)

    Google Scholar 

  17. Henriksen, T.: Design and implementation of the Futhark programming language. Ph.D. thesis, DIKU, University of Copenhagen, November 2017

    Google Scholar 

  18. Henriksen, T., Elsman, M., Oancea, C.E.: Size slicing: a hybrid approach to size inference in Futhark. In: Proceedings of the 3rd ACM SIGPLAN International Workshop on Functional High-Performance Computing, FHPC 2014. ACM (2014)

    Google Scholar 

  19. Henriksen, T., Elsman, M., Oancea, C.E.: Modular acceleration: tricky cases of functional high-performance computing. In: Proceedings of the 7th ACM SIGPLAN International Workshop on Functional High-Performance Computing, FHPC 2018. ACM, New York, September 2018

    Google Scholar 

  20. Henriksen, T., Serup, N.G., Elsman, M., Henglein, F., Oancea, C.E.: Futhark: purely functional GPU-programming with nested parallelism and in-place array updates. In: Proceedings of the 38th ACM SIGPLAN Conference on Programming Language Design and Implementation, PLDI 2017, pp. 556–571. ACM, June 2017

    Google Scholar 

  21. Henriksen, T., Thorøe, F., Elsman, M., Oancea, C.E.: Incremental flattening for nested data parallelism. In: Proceedings of the 24th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP 2019. ACM (2019)

    Google Scholar 

  22. Holk, E., Newton, R., Siek, J., Lumsdaine, A.: Region-based memory management for GPU programming languages: enabling rich data structures on a spartan host. In: Proceedings of the 2014 ACM International Conference on Object Oriented Programming Systems Languages & Applications, OOPSLA 2014, pp. 141–155. ACM, New York, October 2014

    Google Scholar 

  23. Hovgaard, A.K.: Higher-order functions for a high-performance programming language for GPUs. Master’s thesis, Department of Computer Science, Faculty of Science, University of Copenhagen, Universitetsparken 5, DK-2100 Copenhagen, May 2018

    Google Scholar 

  24. Hughes, J.: Why functional programming matters. Comput. J. 32(2), 98–107 (1989)

    Article  Google Scholar 

  25. Johnsson, T.: Lambda lifting: transforming programs to recursive equations. In: Jouannaud, J.-P. (ed.) FPCA 1985. LNCS, vol. 201, pp. 190–203. Springer, Heidelberg (1985). https://doi.org/10.1007/3-540-15975-4_37

    Chapter  Google Scholar 

  26. Jones, M.P.: Composing fractals. J. Funct. Program. 14(6), 715–725 (2004)

    Article  Google Scholar 

  27. Kennedy, A.J.: Functional pearl: pickler combinators. J. Funct. Program. 14(6), 727–739 (2004)

    Article  Google Scholar 

  28. Najd, S., Lindley, S., Svenningsson, J., Wadler, P.: Everything old is new again: quoted domain-specific languages. In: Proceedings of the ACM Workshop on Partial Evaluation and Program Manipulation, PEPM 2016. ACM, January 2016

    Google Scholar 

  29. Peterson, J., Jones, M.: Implementing type classes. In: Proceedings of the ACM SIGPLAN 1993 Conference on Programming Language Design and Implementation, PLDI 1993, pp. 227–236. ACM, New York (1993)

    Google Scholar 

  30. Poulsen, C.B., Mosses, P.D.: Flag-based big-step semantics. J. Log. Algebr. Methods Program. 88, 174–190 (2017)

    Article  MathSciNet  Google Scholar 

  31. Reynolds, J.C.: Definitional interpreters for higher-order programming languages. In: Proceedings of the ACM Annual Conference-Volume 2, pp. 717–740. ACM (1972)

    Google Scholar 

  32. Stratton, J.A., et al.: Parboil: a revised benchmark suite for scientific and commercial throughput computing. Technical report, University of Illinois at Urbana-Champaign, IMPACT-12-01 (2012)

    Google Scholar 

  33. Taha, W., Sheard, T.: MetaML and multi-stage programming with explicit annotations. Theor. Comput. Sci. 248(1), 211–242 (2000). PEPM 1997

    Article  Google Scholar 

  34. Tait, W.W.: Intensional interpretations of functionals of finite type. J. Symb. Log. 32, 198–212 (1967)

    Article  MathSciNet  Google Scholar 

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Authors and Affiliations

  1. DIKU, University of Copenhagen, Copenhagen, Denmark

    Anders Kiel Hovgaard, Troels Henriksen & Martin Elsman

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  1. Anders Kiel Hovgaard
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  2. Troels Henriksen
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  3. Martin Elsman
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Corresponding author

Correspondence to Martin Elsman .

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Editors and Affiliations

  1. Chalmers University of Technology, Gothenburg, Sweden

    Michał Pałka

  2. Chalmers University of Technology, Gothenburg, Sweden

    Magnus Myreen

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Hovgaard, A.K., Henriksen, T., Elsman, M. (2019). High-Performance Defunctionalisation in Futhark. In: Pałka, M., Myreen, M. (eds) Trends in Functional Programming. TFP 2018. Lecture Notes in Computer Science(), vol 11457. Springer, Cham. https://doi.org/10.1007/978-3-030-18506-0_7

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  • DOI: https://doi.org/10.1007/978-3-030-18506-0_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-18505-3

  • Online ISBN: 978-3-030-18506-0

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