Multi-target C++ implementation of parallel skeletons

Proceedings of the 8th Workshop on Parallel/High-Performance Object-Oriented Scientific Computing, POOSC '09

Volumn , Issue , 2009, Pages

  Kirschenmann, Wilfried ^a   Plagne, Laurent ^a   Vialle, Stephane ^b  

^a EDF R AND D   (France)

^b UMI Georgia Tech CNRS 2958   (France)

Author keywords

[No Author keywords available]

Indexed keywords

DATA LAYOUTS; DATA STORAGE; GPU IMPLEMENTATION; LOW COSTS; MULTITARGET;

COMPUTER SCIENCE; DATA STORAGE EQUIPMENT; PARALLEL ARCHITECTURES;

COMPUTER GRAPHICS EQUIPMENT;

EID: 70450194872     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1595655.1595662     Document Type: Conference Paper

References (24)

1. P. An, A. Jula, S. Rus, S. Saunders, T. G. Smith, G. Tanase, N. Thomas, N. M. Amato, and L. Rauchwerger. Stapl: An adaptive, generic parallel c++ library. In H. G. Dietz, editor, LCPC, volume 2624 of Lecture Notes in Computer Science, pages 193-208. Springer, 2001.
2. K. Asanovic, R. Bodik, B. C. Catanzaro, J. J. Gebis, P. Husbands, K. Keutzer, D. A. Patterson, W. L. Plishker, J. Shalf, S. W. Williams, and K. A. Yelick. The landscape of parallel computing research: A view from berkeley. Technical report, EECS Department, University of California, Berkeley, Dec 2006.
3. H. Bischof, S. Gorlatch, and R. Leshchinskiy. Generic parallel programming using c++ templates and skeletons. Domain-Specific Program Generation, pages 107-126, 2004. (Pubitemid 38803769)
4. M. Cole. Algorithmic skeletons: structured management of parallel computation. MIT Press, Cambridge, MA, USA, 1991.
5. cudpp: http://gpgpu.org/developer/cudpp.
6. K. Czarnecki, J. T. Odonnell, J. Striegnitz Walid, and Taha. Dsl implementation in metaocaml, template haskell, and c++. LNCS: Domain-Specific Program Generation, 3016(2):51-72, 2004.
7. G. H. Golub and C. F. Van Loan. Matrix Computations (Johns Hopkins Studies in Mathematical Sciences). The Johns Hopkins University Press, October 1996.
8. Intel. MKL web page can be found from: http://www.intel.com.
9. E. Johnson and D. Gannon. Programming with the hpc++ parallel standard template library. In In Proceedings of the 8th SIAM Conference on Parallel Processing for Scientific Computing (PP'97, 1997.
10. L. Kalé and S. Krishnan. CHARM++: A Portable Concurrent Object Oriented System Based on C++. In A. Paepcke, editor, Proceedings of OOPSLA'93, pages 91-108. ACM Press, September 1993.
11. W. Kirschenmann, L. Plagne, S. Ploix, A. Ponçot, and S. Vialle. Massively parallel solving of 3D simplified PN equations on graphic processing units. In Proceedings of Mathematics, Computational Methods & Reactor Physics, May 2009.
12. MTL4: http://www.osl.iu.edu/research/mtl/mtl4/.
13. Microsoft. Microsoft PPL web page can be found from: http://msdn. microsoft.com/en-us/concurrency/default.aspx.
14. Netlib. BLAS: http://www.netlib.org/blas.
15. NVIDIA. CUDA Programming Guide 2.0, July 2008.
16. L. Plagne and A. Ponçcot. Generic programming for deterministic neutron transport codes. In Proceedings of Mathematics and Computation, Supercomputing, Reactor Physics and Nuclear and Biological Applications, Palais des Papes, Avignon, France, September 2005.
17. P. Plauger, M. Lee, D. Musser, and A. A. Stepanov. C++ Standard Template Library. Prentice Hall PTR, Upper Saddle River, NJ, USA, 2000.
18. J. Reinders. Intel threading building blocks. O'Reilly & Associates, Inc., Sebastopol, CA, USA, 2007.
19. B. Stroustrup. The C++ Programming Language. Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA, 2000.
20. G. Tanase, C. Raman, M. Bianco, N. M. Amato, and L. Rauchwerger. Associative parallel containers in stapl. In V. S. Adve, M. J. Garzarán, and P. Petersen, editors, LCPC, volume 5234 of Lecture Notes in Computer Science, pages 156-171. Springer, 2007.
21. Thrust: http://code.google.com/p/thrust/.
22. T. L. Veldhuizen. Arrays in blitz++. In Proceedings of the 2nd International Scientific Computing in Object-Oriented Parallel Environments (ISCOPE'98), Lecture Notes in Computer Science. Springer-Verlag, 1998.
23. R. C. Whaley, A. Petitet, and J. Dongarra. Automated empirical optimizations of software and the ATLAS project. Parallel Computing, 27(1-2):3-25, 2001.
24. W. A. Wulf and S. A. McKee. Hitting the memory wall: implications of the obvious. SIGARCH Comput. Archit. News, 23(1):20-24, 1995.