Scout: a data-parallel programming language for graphics processors

Parallel Computing

Volumn 33, Issue 10-11, 2007, Pages 648-662

  McCormick, Patrick ^a   Inman, Jeff ^a   Ahrens, James ^a   Mohd Yusof, Jamaludin ^a   Roth, Greg ^b   Cummins, Sharen ^a  

^a LOS ALAMOS NATIONAL LABORATORY   (United States)

^b UNIVERSITY OF UTAH   (United States)

Author keywords

Data parallel programming; Graphics processors; Heterogeneous computing; Visualization

Indexed keywords

COMPUTER HARDWARE; COMPUTER SOFTWARE; DIGITAL ARITHMETIC; PRINTERS (COMPUTER);

DATA-PARALLEL PROGRAMMING; GRAPHICS PROCESSORS; HETEROGENEOUS COMPUTING;

COMPUTER PROGRAMMING LANGUAGES;

EID: 35948940866     PISSN: 01678191     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.parco.2007.09.001     Document Type: Article

References (40)

1. Aho A., Sethi R., and Ullman J. Compilers: Principles, Techniques, and Tools (1988), Addison Wesley
2. Advanced Micro Devices Inc., ATI CTM Guide - Technical Reference Manual. , 2006.
3. Advanced Micro Devices Inc., Torrenza Technology. , 2006.
4. Blelloch G. Vector Models for Data-parallel Computing (1990), MIT Press, Cambridge, MA
5. Blelloch G., Chatterjee S., Hardwick J.C., Sipelstein J., and Zagha M. Implementation of a portable nested data-parallel language. Journal of Parallel and Distributed Computing 21 1 (1994) 4-14
6. Blelloch G. Scans as primitive parallel operations. IEEE Transactions on Computers 38 11 (1989) 1526-1538
7. Buck I., Foley T., Horn D., Sugerman J., Fatahalian K., Houston M., and Hanrahan P. Brook for GPUs: stream computing on graphics hardware. ACM Transactions on Graphics 23 3 (2004) 777-786
8. B.L. Chamberlain, The Design and Implementation of a Region-based Parallel Language, PhD Thesis, University of Washington, November 2001.
9. Chamberlain B.L., Callahan D., and Zima H.P. Parallel programmability and the Chapel language. International Journal of High Performance Computing Applications 21 3 (2007) 291-312
10. B. Corrie, P. Mackerras, Data Shaders, in: VIS'93: Proceedings of the 4th Conference on Visualization 1993, 1993, pp. 275-282.
11. R.A. Crawfis, M.J. Allison, A scientific visualization synthesizer, in: VIS'91: Proceedings of the 2nd Conference on Visualization, 1991, pp. 262-267.
12. GPGPU, General-purpose Computation Using Graphics Hardware, http://www.gpgpu.org, 2007.
13. Harris M. Mapping computational concepts to GPUs. In: Pharr M. (Ed). GPU Gems 2 (2005), Addison Wesley 493-508 (Chapter 31)
14. Horn D. Stream reduction operations for GPGPU applications. In: Pharr M. (Ed). GPU Gems 2 (2005), Addison Wesley 573-589 (Chapter 36)
15. Intel Inc., Geneseo: PCI Express Technology Advancement, , 2006.
16. Iverson K. A Programming Language (1962), Wiley, New York
17. Karma A., and Rappel W.-J. Quantitative phase-field modeling of dendritic growth in two and three dimensions. Physical Review E 57 (1998) 4323-4349
18. J. Kessenich, D. Baldwin, R. Rost, The OpenGL Shading Language Version 1.10.59, , April, 2004.
19. Mark W., Glanville R., Akeley K., and Kilgard M. Cg: a system for programming graphics hardware in a C-like language. ACM Transactions on Graphics 22 3 (2003) 896-907
20. Cytron R., Ferrante J., Rosen B., Wegman M.N., and Zadeck F.K. Efficiently computing static single assignment form and the control dependence graph. ACM Transactions on Programming Languages and Systems 13 4 (1991) 451-490
21. Lefohn A.E., Kniss J., Strzodka R., Sengupta S., and Owens J.D. Glift: an abstraction for generic, efficient GPU data structures. ACM Transactions on Graphics 26 1 (2006) 60-99
22. Lucas P., Fritz N., and Wilhelm R. The CGiS compiler. Proceedings of the 15th International Conference on Compiler Construction. Lecture Notes in Computer Science vol. 3923 (March 2006), Springer 105-108
23. M. McCool, Data-parallel Programming on the Cell BE and the GPU using the RapidMind Development Platform, GSPx Multicore Applications Conference, Santa Clara, October 31-November 2, 2006, .
24. P. McCormick, J. Inman, J. Ahrens, C. Hansen, G. Roth, Scout: a hardware-accelerated system for quantitatively driven visualization and analysis, in: IEEE Visualization 2004, October 2004, pp. 171-178.
25. Microsoft Corporation, Microsoft High-Level Shading Language, , 2005.
26. NVIDIA Corporation, NVIDIA CUDA Homepage, , 2007.
27. J.D. Owens, D. Luebke, N. Govindaraju, M. Harris, J. Krüger, A.E. Lefohn, T. Purcell, A survey of general-purpose computation on graphics hardware, in: Computer Graphics Forum, March 2007, pp. 80-113.
28. A. Riffel, A. LeFohn A., K. Vidimce, M. Leone, J.D. Owens, Mio: fast multipass partitioning via priority-based instruction scheduling, in: Graphics Hardware 2004, August 2004, pp. 35-44.
29. SAMRAI (Structured Adaptive Mesh Refinement Application Infrastructure) Homepage, www.llnl.gov/CASC/SAMRAI, 2007.
30. Shreiner D., Woo M., Neider J., and Davis T. OpenGL Programming Guide: the Official Guide to Learning OpenGL (2006), Addison-Wesley
31. S. Sengupta, A.E. Lefohn, J.D. Owens, A work-efficient step-efficient prefix sum algorithm, in: Proceedings of the Workshop on Edge Computing Using New Commodity Architectures, August 2007, pp. D-26-27.
32. Sipelstein J., and Blelloch G.E. Collection-oriented languages. Proceedings of the IEEE 79 4 (1991) 504-523
33. D. Tarditi, S. Puri, J. Oglesby, Accelerator: using data-parallelism to program GPUS for General Purpose Uses, in: Proceedings of the 12th International Conference on Architectural Support for Programming Languages and Operating Systems, October 2006, pp. 325-335.
34. * User's Guide, 1991.
35. S. Sengupta, M. Harris, Y. Zhang, J.D. Owens, Scan Primitives for GPU, in: Computing Graphics Hardware 2007, August 2007, pp. 97-106.
36. Dennis J.B. Data flow supercomputers. Computer 13 11 (1980) 48-56
37. Dyer D.S. Visualization: a dataflow toolkit for visualization. IEEE Computer Graphics & Applications 10 4 (1990) 60-69
38. W.J. Schroeder, K.M. Martin, W.E. Lorensen, The design and implementation of an object-oriented toolkit for 3D graphics and visualization, in: Proceedings of Visualization'96, 1996, pp. 93-100.
39. G. Abram, L. Treinish, An extended data-flow architecture for data analysis and visualization, in: Proceedings of Visualization'95, 1995, pp. 363-370.
40. Ahrens J., Brislwan K., Martin K., Geveci B., Law C.C., and Papka M. Large-scale data visualization using parallel data streaming. IEEE Computer Graphics & Applications 21 4 (2001) 34-41