Parallel computing of kernel density estimation with different multi-core programming models

Proceedings of the 2013 21st Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, PDP 2013

Volumn , Issue , 2013, Pages 77-85

  Michailidis, Panagiotis D ^a   Margaritis, Konstantinos G ^b  

^a UNIVERSITY OF WESTERN MACEDONIA   (Greece)

^b UNIVERSITY OF MACEDONIA   (Greece)

Author keywords

Kernel density estimation; Multi core; Parallel computing; parallel programming

Indexed keywords

KERNEL DENSITY ESTIMATION; KERNEL ESTIMATION; LARGE DATASETS; MULTI CORE; MULTI-CORE PLATFORMS; PROBABILISTIC DENSITY; PROGRAMMING FRAMEWORK; PROGRAMMING MODELS;

APPLICATION PROGRAMMING INTERFACES (API); MICROPROCESSOR CHIPS; PARALLEL ARCHITECTURES; PARALLEL PROCESSING SYSTEMS; PARALLEL PROGRAMMING; STATISTICS;

MULTICORE PROGRAMMING;

EID: 84877679029     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/PDP.2013.20     Document Type: Conference Paper

References (27)

1. Intel Cilk Plus, 2012. http://software.intel.com/en-us/articles/intel- cilk-plus/.
2. Intel Threading Building Blocks, 2012. http://threadingbuildingblocks. org/.
3. Kernel density estimation, 2012. http://en.wikipedia.org/wiki/Kernel- density-estimation.
4. The openMP API specification for parallel programming, 2012. http://openmp.org/wp/.
5. N. M. Adams, S. P. J. Kirby, P. Harris, and D. B. Clegg. A review of parallel processing for statistical computation. Statistics and Computing, 6:37-49, 1996. (Pubitemid 126716898)
6. M. Aldinucci, M. Danelutto, P. Kilpatrick, M. Meneghin, and M. Torquati. Accelerating code on multi-cores with FastFlow. In Proceedings of the 17th International Conference on Parallel processing - Volume Part II, Euro-Par'11, pages 170-181, Berlin, Heidelberg, 2011. Springer-Verlag.
7. M. Aldinucci, M. Danelutto, P. Kilpatrick, and M. Torquati. Programming Multi-core and Many-core Computing Systems, chapter FastFlow: high-level and efficient streaming on multi-core. Wiley, 2011.
8. D. A. Bader and J. JaJa. Simple: A methodology for programming high performance algorithms on clusters of symmetric multiprocessors (SMPs). Journal of Parallel and Distributed Computing, 58:92-108, 1999.
9. D. A. Bader, V. Kanade, and K. Madduri. SWARM: A Parallel Programming Framework for Multicore Processors. In Parallel and Distributed Processing Symposium, 2007. IPDPS 2007, pages 1-8, 2007.
10. R. D. Blumofe, C. F. Joerg, B. C. Kuszmaul, C. E. Leiserson, K. H. Randall, and Y. Zhou. Cilk: An efficient multithreaded runtime system. In Proceedings of the Fifth ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), pages 207-216, Santa Barbara, California, July 1995.
11. D. Buttlar, J. Farrell, and B. Nichols. PThreads Programming: A POSIX Standard for Better Multiprocessing. O'Reilly Media, 1996.
12. M. Creel. User-friendly parallel computations with econometric examples. Comput. Econ., 26(2):107-128, Oct. 2005. (Pubitemid 41631015)
13. M. Creel and W. L. Goffe. Multi-core CPUs, Clusters, and Grid Computing: A Tutorial. Comput. Econ., 32(4):353-382, Nov. 2008.
14. T. Deepak Shekhar, K. Varaganti, R. Suresh, R. Garg, and R. Ramamoorthy. Comparison of parallel programming models for multicore architectures. In 2011 IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW), pages 1675-1682, May 2011.
15. A. V. Dobrovidov and I. M. Ruds'Ko. Bandwidth selection in nonparametric estimator of density derivative by smoothed cross-validation method. Autom. Remote Control, 71(2):209-224, Feb. 2010.
16. A. Elgammal, R. Duraiswami, and L. S. Davis. Efficient kernel density estimation using the fast gauss transform with applications to color modeling and tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25:1499-1504, 2003.
17. J. Fernandez, M. Anguita, S. Mota, A. Caas, E. Ortigosa, and F. Rojas. MPI toolbox for octave. In VecPar'2004, 2004. http://atc.ugr.es/ javier/investigacion/papers/VecPar04.pdf.
18. P. Kegel, M. Schellmann, and S. Gorlatch. Comparing programming models for medical imaging on multi-core systems. Concurrency and Computation: Practice and Experience, 23(10):1051-1065, 2011.
19. J. Klemel. Smoothing of Multivariate Data: Density Estimation and Visualization. Wiley Publishing, 1st edition, 2009.
20. E. J. Kontoghiorghes. Parallel Algorithms for Linear Models - Numerical Methods and Estimation Problems. Kluwer Academic Publishers, 2000.
21. E. J. Kontoghiorghes. Handbook of Parallel Computing and Statistics. Chapman & Hall/CRC, 2005.
22. S. Lukasik. Parallel computing of kernel density estimates with mpi. In Proceedings of the 7th International Conference on Computational Science, Part III: ICCS 2007, ICCS '07, pages 726-733, Berlin, Heidelberg, 2007. Springer-Verlag.
23. J. Racine. Parallel distributed kernel estimation. Comput. Stat. Data Anal., 40(2):293-302, Aug. 2002. (Pubitemid 35022463)
24. J. Reinders. Intel Threading Building Blocks - Outfitting C++ for Multi-core Processor Parallelism. O'Reilly, 2007.
25. B. Silverman. Density Estimation for Statistics and Data Analysis (Chapman & Hall/CRC Monographs on Statistics & Applied Probability). Chapman and Hall/CRC, 1 edition, Apr. 1986.
26. B. W. Silverman. Algorithm AS 176: Kernel density estimation using the fast Fourier transform. Applied Statistics, 31(1):93-99, 1982.
27. M. P. Wand and M. C. Jones. Kernel Smoothing (Chapman & Hall/CRC Monographs on Statistics & Applied Probability). Chapman and Hall/CRC, 1 edition, Dec. 1994.