Ypnos: Declarative, parallel structured grid programming

DAMP'10 - Proceedings of the 2010 ACM SIGPLAN Workshop on Declarative Aspects of Multicore Programming

Volumn , Issue , 2010, Pages 15-24

  Orchard, Dominic A ^a   Bolingbroke, Max ^a   Mycroft, Alan ^a  

^a UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

Comonads; EDSL; Parallelism; Stencils; Structured grids; Ypnos

Indexed keywords

COMONADS; DOMAIN SPECIFIC LANGUAGES; LANGUAGE SEMANTICS; PARALLEL IMPLEMENTATIONS; PARALLELISATION; SEQUENTIAL OPERATIONS; STRUCTURED GRID; THEORETICAL ASPECTS; TIME AND SPACE;

LINGUISTICS; PARALLEL PROGRAMMING; PROBLEM ORIENTED LANGUAGES; TECHNICAL PRESENTATIONS;

STRUCTURED PROGRAMMING;

EID: 77950901120     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1708046.1708053     Document Type: Conference Paper

References (31)

1. ACE Associated Compiler Experts bv. Parallelization using Polyhedral Analysis, 2008, last accessed September 2009. https://www.opencosy.org/node/37.
2. K. Asanovic, R. Bodik, Demmel, et al. The Parallel Computing Laboratory at U.C. Berkeley: A research agenda based on the Berkeley view. Technical Report UCB/EECS-2008-2023, EECS Department, University of California, Berkeley, Mar 2008.
3. E. A. Ashcroft, A. A. Faustini, R. Jagannathan, and W. W. Wadge. Multidimensional programming. Oxford University Press, Oxford, UK, 1995. ISBN 0-19-507597-8.
4. R. F. Barret, P. C. Roth, and S. W. Poole. Finite Difference Stencils Implemented Using Chapel. Technical Report TM-2007/119, 2007.
5. C. Bastoul, A. Cohen, S. Girbal, S. Sharma, and O. Temam. Putting Polyhedral Loop Transformations to Work. Research Report RR-4902, INRIA, 2003.
6. M. J. Berger. Adaptive mesh refinement for hyperbolic partial differential equations. PhD thesis, Stanford, CA, USA, 1982.
7. L. Dagum and R. Menon. OpenMP: An Industry-Standard API for Shared-Memory Programming. IEEE Comput. Sci. Eng., 5(1):46-55, 1998. ISSN 1070-9924.
8. E.W. Evans, S. P. Johnson, P. F. Leggett, andM. Cross. Automatic and effective multi-dimensional parallelisation of structured mesh based codes. Parallel Comput., 26(6):677-703, 2000. ISSN 0167-8191.
9. C. Gerald and P. Wheatley. Applied Numerical Analysis. Pearson Education, Addison Wesley, San Francisco, 2004.
10. W. Hackbusch. Multi-grid methods and applications. Volume 4 of Springer series in computational mathematics. Springer, 1985.
11. T. Halfhill. Parallel Processing with CUDA. Microprocessor Report, Januray 2008.
12. M. Harris. Mapping computational concepts to GPUs. In SIGGRAPH '05: ACM SIGGRAPH 2005 Courses, page 50, New York, NY, USA, 2005. ACM.
13. P. Hudak and A. Bloss. The aggregate update problem in functional programming systems. In POPL '85: Proceedings of the 12th ACM SIGACT-SIGPLAN symposium on Principles of programming languages, pages 300-314, New York, NY, USA, 1985. ACM.
14. G. Huet. The Zipper. J. Funct. Program., 7(5):549-554, 1997. ISSN 0956-7968.
15. R. Jagannathan, C. Dodd, and I. Agi. GLU: A high-level system for granular data-parallel programming. Concurrency: Practice and Experience, 9(1):63-83, 1997.
16. S. Lee, M. M. Chakravarty, V. Grover, and G. Keller. GPU Kernels as Data-Parallel Array Computations in Haskell. 2009.
17. D. Leijen and E. Meijer. Parsec: Direct style monadic parser combinators for the real world. Technical Report, 2001.
18. G. Mainland. Why It's Nice to be Quoted: Quasiquoting for Haskell. In Haskell '07: Proceedings of the ACM SIGPLAN workshop on Haskell workshop, pages 73-82, New York, NY, USA, 2007. ACM. ISBN 978-1-59593-674-5.
19. W. R. Mark, R. S. Glanville, K. Akeley, and M. J. Kilgard. Cg: a system for programming graphics hardware in a C-like language. In SIGGRAPH '03: ACMSIGGRAPH 2003 Papers, pages 896-907, New York, NY, USA, 2003. ACM. ISBN 1-58113-709-5.
20. E. Moggi. Notions of computation and monads. Inf. Comput., 93(1):55-92, 1991. ISSN 0890-5401.
21. N. Mukherjee and J. R. Gurd. A comparative analysis of four parallelisation schemes. In ICS '99: Proceedings of the 13th international conference on Supercomputing, pages 278-285, New York, NY, USA, 1999. ACM. ISBN 1-58113-164-X.
22. A. Munshi. OpenCL: Parallel computing on the GPU and CPU. presentation at SIGGRAPH 2008 http://s08.idav.ucdavis.edu/munshi-opencl.pdf.
23. S. Patidar, S. Bhattacharjee, J. M. Singh, and P. J. Narayanan. Exploiting the Shader Model 4.0 Architecture, March 2007. Technical Report IIIT/TR/2007/145, 2007
24. D. Piponi. Evaluating cellular automata is comonadic, December 2006, Last retrieved September 2009. http://blog.sigfpe.com/2006/12/evaluating-cellular- automata-is.html.
25. J. Power and H. Watanabe. Combining a monad and a comonad. Theor. Comput. Sci., 280(1-2):137-162, 2002. ISSN 0304-3975.
26. M. Snir and S. Otto. MPI-The Complete Reference: The MPI Core. MIT Press, Cambridge, MA, USA, 1998. ISBN 0262692155.
27. D. Stewart. Domain Specific Languages for Domain Specific Problems. In Workshop on Non-Traditional Programming Models for High-Performance Computing, LACSS, 2009.
28. T. Uustalu and V. Vene. The Essence of Dataflow Programming. Lecture Notes in Computer Science, 4164:135-167, November 2006.
29. T. Uustalu and V. Vene. Comonadic Notions of Computation. Electron. Notes Theor. Comput. Sci., 203(5):263-284, 2008. ISSN 1571-0661.
30. W. Wadge and E. Ashcroft. LUCID, the dataflow programming language. Academic Press Professional, Inc., San Diego, CA, USA, 1985. ISBN 0-12-729650-6.
31. P. Wadler. Linear Types Can Change the World! In Programming Concepts and Methods. North, 1990.