skip to main content
10.1145/1401132.1401152acmconferencesArticle/Chapter ViewAbstractPublication PagessiggraphConference Proceedingsconference-collections
research-article

Scalable parallel programming with CUDA

Published:11 August 2008Publication History

ABSTRACT

Is CUDA the parallel programming model that application developers have been waiting for?

References

  1. NVIDIA. 2007. CUDA Technology; http://www.nvidia.com/CUDA.Google ScholarGoogle Scholar
  2. NVIDIA. 2007. CUDA Programming Guide 1.1; http://developer.download.nvidia.com/compute/cuda/1_1/NVIDIA_CUDA_Programming_Guide_1.1.pdf.Google ScholarGoogle Scholar
  3. Stratton, J. A., Stone, S. S., Hwu, W. W. 2008. M-CUDA: An efficient implementation of CUDA kernels on multicores. IMPACT Technical Report 08-01, University of Illinois at Urbana-Champaign, (February).Google ScholarGoogle Scholar
  4. See reference 3.Google ScholarGoogle Scholar
  5. Buck, I., Foley, T., Horn, D., Sugerman, J., Fatahalian, K., Houston, M., Hanrahan, P. Brook for GPUs: Stream computing on graphics hardware. 2004. Proceedings of SIGGRAPH (August): 777--786; http://doi.acm.org/10.1145/1186562.1015800. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Stone, S. S., Yi, H., Hwu, W. W., Haldar, J. P., Sutton, B. P., Liang, Z.-P. 2007. How GPUs can improve the quality of magnetic resonance imaging. The First Workshop on General-Purpose Processing on Graphics Processing Units (October).Google ScholarGoogle Scholar
  7. Stone, J. E., Phillips, J. C., Freddolino, P. L., Hardy, D. J., Trabuco, L. G., Schulten, K. 2007. Accelerating molecular modeling applications with graphics processors. Journal of Computational Chemistry 28(16): 2618--2640; http://dx.doi.org/10.1002/jcc.20829.Google ScholarGoogle ScholarCross RefCross Ref
  8. Nyland, L., Harris, M., Prins, J. 2007. Fast n-body simulation with CUDA. In GPU Gems 3. H. Nguyen, ed. Addison-Wesley.Google ScholarGoogle Scholar
  9. Golub, G. H., and Van Loan, C. F. 1996. Matrix Computations, 3rd edition. Johns Hopkins University Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Buatois, L., Caumon, G., Lévy, B. 2007. Concurrent number cruncher: An efficient sparse linear solver on the GPU. Proceedings of the High-Performance Computation Conference (HPCC), Springer LNCS. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Sengupta, S., Harris, M., Zhang, Y., Owens, J. D. 2007. Scan primitives for GPU computing. In Proceedings of Graphics Hardware (August): 97--106. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. See Reference 3.Google ScholarGoogle Scholar

Index Terms

  1. Scalable parallel programming with CUDA

              Recommendations

              Comments

              Login options

              Check if you have access through your login credentials or your institution to get full access on this article.

              Sign in
              • Published in

                cover image ACM Conferences
                SIGGRAPH '08: ACM SIGGRAPH 2008 classes
                August 2008
                5354 pages
                ISBN:9781450378451
                DOI:10.1145/1401132

                Copyright © 2008 ACM

                Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

                Publisher

                Association for Computing Machinery

                New York, NY, United States

                Publication History

                • Published: 11 August 2008

                Permissions

                Request permissions about this article.

                Request Permissions

                Check for updates

                Qualifiers

                • research-article

                Acceptance Rates

                Overall Acceptance Rate1,822of8,601submissions,21%

                Upcoming Conference

                SIGGRAPH '24

              PDF Format

              View or Download as a PDF file.

              PDF

              eReader

              View online with eReader.

              eReader