Fast, processor-cardinality agnostic PRNG with a tracking application

Proceedings - 6th Indian Conference on Computer Vision, Graphics and Image Processing, ICVGIP 2008

Volumn , Issue , 2008, Pages 171-178

  Janowczyk, Andrew ^a   Chandran, Sharat ^a   Aluru, Srinivas ^b  

^a INDIAN INSTITUTE OF TECHNOLOGY BOMBAY   (India)

^b IOWA STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CARDINALITY; DEVELOPMENT TIME; EXECUTION TIME; HIGH QUALITIES; LEARNING COMMUNITIES; MERSENNE TWISTERS; PARALLEL COMPUTING; PARALLEL HARDWARES; PARTICLE FILTERS; PROCESSING RESOURCES; RANDOM NUMBERS; STATE-OF-THE ARTS; TRACKING APPLICATIONS; VISION ALGORITHMS; VISION APPLICATIONS;

APPLICATIONS; COMPUTER VISION; DISTRIBUTED COMPUTER SYSTEMS; IMAGING SYSTEMS; LEARNING ALGORITHMS; PARALLEL ALGORITHMS; PARALLEL PROCESSING SYSTEMS; SOFTWARE PROTOTYPING; TELLURIC PROSPECTING;

RANDOM NUMBER GENERATION;

EID: 65249146502     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICVGIP.2008.90     Document Type: Conference Paper

References (11)

1. S. Aluru. Lagged Fibonacci random number generators for distributed memory parallel computers. J. Parallel Distrib. Comput., 45(1):1-12, 1997.
2. S. Arulampalam, S. Maskell, and N. Gordon. A tutorial on particle filters for online nonlinear non-Gaussian Bayesian tracking. IEEE Transactions on Signal Processing, 50:174-188, 2002.
3. R. B. D'Agostino and M. A. Stephens, editors. Goodness-of-fit techniques. Marcel Dekker, Inc., New York, USA, 1986.
4. D. E. Knuth. The art of computer programming. Addison-Wesley Longman Publishing Co., Inc., Boston, USA, 1997.
5. G. Marsaglia. A current view of random number generators. pages 3-10, 1985.
6. G. Marsaglia. The marsaglia random number cdrom including the diehard battery of tests of randomness, 1995. http://www.stat.fsu.edu/pub/diehard.
7. M. Matsumoto and T. Nishimura. Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator. ACM Trans. Model. Comput. Simul., 8(1):3-30, 1998.
8. M. Matsumoto and T. Nishimura. Dynamic creation of pseudorandom number generators. Monte Carlo and Quasi-Monte Carlo Methods 1998, pages 56-69, 2000.
9. NVIDIA CUDA. Compute unified device architecture programming guide version 1.1. 2007.
10. M. Sussman, W. Crutchfield, and M. Papakipos. Pseudorandom number generation on the GPU. In Proceedings of the 21st ACM SIGGRAPH/EUROGRAPHICS symposium on Graphics hardware, pages 87-94, New York, USA, 2006. ACM.
11. S. Tzeng and L.-Y.Wei. Parallel white noise generation on a GPU via cryptographic hash. In Proceedings of the 2008 symposium on Interactive 3D graphics and games, pages 79-87, New York, USA, 2008. ACM.