Compressing the incompressible with ISABELA: In-situ reduction of spatio-temporal data

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6852 LNCS, Issue PART 1, 2011, Pages 366-379

  Lakshminarasimhan, Sriram ^a,b   Shah, Neil ^a   Ethier, Stephane ^c   Klasky, Scott ^b   Latham, Rob ^d   Ross, Rob ^d   Samatova, Nagiza F ^a,b  

^a NORTH CAROLINA STATE UNIVERSITY   (United States)

^b OAK RIDGE NATIONAL LABORATORY   (United States)

^c PRINCETON PLASMA PHYSICS LABORATORY   (United States)

^d ARGONNE NATIONAL LABORATORY   (United States)

Author keywords

B spline; Data intensive Application; High Performance Computing; In situ Processing; Lossy Compression

Indexed keywords

B-SPLINE; DATA-INTENSIVE APPLICATION; HIGH PERFORMANCE COMPUTING; IN-SITU; LOSSY COMPRESSIONS;

COMPUTER SOFTWARE SELECTION AND EVALUATION; DATA REDUCTION; IMAGE COMPRESSION; SPLINES; VISUALIZATION;

DATA VISUALIZATION;

EID: 80052343989     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-23400-2_34     Document Type: Conference Paper

References (18)

1. Abbasi, H., Lofstead, J., Zheng, F., Klasky, S., Schwan, K., Wolf, M.: Extending I/O through high performance data services. In: Cluster Computing, Austin, TX, IEEE International (September 2007)
2. De Boor, C.: A Practical Guide to Splines. Springer, Heidelberg (1978)
3. Burtscher, M., Ratanaworabhan, P.: FPC: A high-speed compressor for double-precision floating-point data (2009), http://www.csl.cornell.edu/ ~burtscher/research/FPC/
4. Chou, J., Piegl, L.: Data reduction using cubic rational B-splines. IEEE Comput. Graph. Appl. 12, 60-68 (1992)
5. Cover, T.M., Thomas, J.: Elements of information theory. Wiley-Interscience, New York (1991)
6. Frazier, M.W.: An introduction to Wavelets through linear algebra, p. 501. Springer, Heidelberg (1999)
7. He, X., Shi, P.: Monotone B-spline smoothing. Journal of the American Statistical Association 93(442), 643-650 (1998)
8. Isenburg, M., Lindstrom, P., Snoeyink, J.: Lossless compression of predicted floating-point geometry. Computer-Aided Design 37(8), 869-877 (2005); CAD 2004 Special Issue: Modelling and Geometry Representations for CAD
9. Lee, S., Wolberg, G., Shin, S.Y.: Scattered data interpolation with multilevel B-splines. IEEE Trans. on Viz. and Comp. Graphics 3(3), 228-244 (1997)
10. Lindstrom, P., Isenburg, M.: Fast and efficient compression of floating-point data. IEEE Trans. on Viz. and Comp. Graphics 12(5), 1245-1250 (2006)
11. Lofstead, J., Zheng, F., Klasky, S., Schwan, K.: Adaptable, metadata rich IO methods for portable high performance IO. In: IPDPS 2009, Rome, Italy (May 2009)
12. Ma, K., Wang, C., Yu, H., Tikhonova, A.: In-situ processing and visualization for ultrascale simulations. Journal of Physics: Conference Series 78(1), 012043 (2007)
13. Ratanaworabhan, P., Ke, J., Burtscher, M.: Fast lossless compression of scientific floating-point data. In: Proc. of the DCC (2006)
14. Sayood, K.: Introduction to data compression. Morgan Kaufmann Publishers Inc., San Francisco (1996)
15. Wang, W.X., al, e.: Gyro-kinetic simulation of global turbulent transport properties in Tokamak experiments. Physics of Plasmas 13(9), 092505 (2006)
16. Welch, T.A.: A technique for high-performance data compression. Computer 17, 8-19 (1984)
17. Wold, S.: Spline functions in data analysis. American Statistical Association and American Society for Quality 16(1), 1-11 (1974)
18. Zheng, F., al, e.: PreDatA-preparatory data analytics on peta-scale machines. In: IPDPS, Atlanta, GA (April 2010)