Abstract
State of the art graphics processors provide high processing power and furthermore, the high programmability of GPUs offered by frameworks like CUDA increases their usability as high-performance co-processors for general-purpose computing. Sorting is well-investigated in Computer Science in general, but (because of this new field of application for GPUs) there is a demand for high-performance parallel sorting algorithms that fit to the characteristics of modern GPU-architecture.
We present a high-performance in-place implementation of Batcher’s bitonic sorting networks for CUDA-enabled GPUs. We adapted bitonic sort for arbitrary input length and assigned compare/exchange-operations to threads in a way that decreases low-performance global-memory access and thereby greatly increases the performance of the implementation.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Kapasi, U.J., Dally, W.J., Rixner, S., Mattson, P.R., Owens, J.D., Khailany, B.: Efficient conditional operations for data-parallel architectures. In: MICRO 33: Proceedings of the 33rd Annual ACM/IEEE International Symposium on Microarchitecture, pp. 159–170. ACM, New York (2000)
Purcell, T.J., Donner, C., Cammarano, M., Jensen, H.W., Hanrahan, P.: Photon mapping on programmable graphics hardware. In: HWWS 2003: Proceedings of the ACM SIGGRAPH/EUROGRAPHICS Conference on Graphics Hardware, Aire-la-Ville, Switzerland, pp. 41–50. Eurographics Association (2003)
Kipfer, P., Segal, M., Westermann, R.: Uberflow: a gpu-based particle engine. In: HWWS 2004: Proceedings of the ACM SIGGRAPH/EUROGRAPHICS Conference on Graphics Hardware, pp. 115–122. ACM, New York (2004)
Govindaraju, N., Raghuvanshi, N., Henson, M., Manocha, D.: A cache-efficient sorting algorithm for database and data mining computations using graphics processors. Technical report, University of North Carolina-Chapel Hill (2005)
Greb, A., Zachmann, G.: Gpu-abisort: optimal parallel sorting on stream architectures. In: 20th International on Parallel and Distributed Processing Symposium, IPDPS 2006 (2006)
Batcher, K.: Sorting networks and their applications. In: AFIPS Spring Joint Comput. Conf. (1967)
Harris, M., Sengupta, S., Owens, J.D.: Parallel prefix sum (scan) with cuda. In: GPU Gems 3. Addison-Wesley, Reading (2007)
Grand, S.L.: Broad-phase collision detection with cuda. In: GPU Gems, vol. 3, Addison-Wesley, Reading (2007)
He, B., Govindaraju, N.K., Luo, Q., Smith, B.: Efficient gather and scatter operations on graphics processors. In: SC 2007: Proceedings of the 2007 ACM/IEEE Conference on Supercomputing, pp. 1–12. ACM, New York (2007)
Sengupta, S., Harris, M., Zhang, Y., Owens, J.D.: Scan primitives for gpu computing. In: GH 2007: Proceedings of the 22nd ACM SIGGRAPH/EUROGRAPHICS Symposium on Graphics Hardware, Aire-la-Ville, Switzerland, pp. 97–106. Eurographics Association (2007)
Cederman, D., Tsigas, P.: A practical quicksort algorithm for graphics processors. In: Halperin, D., Mehlhorn, K. (eds.) Esa 2008. LNCS, vol. 5193, pp. 246–258. Springer, Heidelberg (2008)
Sintorn, E., Assarsson, U.: Fast parallel gpu-sorting using a hybrid algorithm, Orlando, FL, USA, vol. 68, pp. 1381–1388. Academic Press, Inc., London (2008)
Satish, N., Harris, M., Garland, M.: Designing efficient sorting algorithms for manycore gpus. In: Proceedings 23rd IEEE International Parallel and Distributed Processing Symposium (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Peters, H., Schulz-Hildebrandt, O., Luttenberger, N. (2010). Fast In-Place Sorting with CUDA Based on Bitonic Sort. In: Wyrzykowski, R., Dongarra, J., Karczewski, K., Wasniewski, J. (eds) Parallel Processing and Applied Mathematics. PPAM 2009. Lecture Notes in Computer Science, vol 6067. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14390-8_42
Download citation
DOI: https://doi.org/10.1007/978-3-642-14390-8_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14389-2
Online ISBN: 978-3-642-14390-8
eBook Packages: Computer ScienceComputer Science (R0)