Telephone: 1-510-486-6609
E-mail: or
Mailstop 50B-3238, 1 Cyclotron Road, Berkeley, CA 94720, USA
武克胜      Kesheng Wu      (John)

Research Interests
* Analysis and management of large datasets
* Parallel distributed software systems design and implementation
* Component architecture for scientific software
* Performance tuning for large distributed software

Make It A Bit Faster with FastBit
* FastBit [Publications]: an efficient compressed bitmap index technology for data intensive sciences. This project addresses the challenges of efficiently searching growing amounts of data collected/generated by various scientific applications, such as high-energy physics, combustion, astrophysics, and network traffic analysis. The FastBit software has received an R&D 100 Award; here is a photo from the award receiption.
* Connected Component Labeling [Publications]: an efficient connected component labeling algorithm. This grows out our work on feature tracking for a combustion data analysis. The key new insight is that there is a way to make use of an implicit union-find data structure to speed up the connected component labeling algorithms, which in turn leads to faster algorithms for finding regions of interest. In particular, using compressed bitmaps as representations of points in the regions of interest, we can find the regions in time that is proportional to the the number of points on the boundary of the regions. This is faster than the best iso-contouring algorithms and much faster than similar region finding algorithms. This is also a basis of some of the work on visualization and visual analytics.
* DEX [Publications]: a query-based visualization tool. This project provides a new visualization capability based on the FastBit technology and the fast connected component labeling technology. This effective combination was first demonstrated on a project of analyzing combustion simulation data. It is extensively documented in our paper at IEEE Vis 2005, and also appeared in a SciDAC review report about the Scientific Data Management Center.
* TRLan [Publications]: Thick-restart Lanczos method for symmetric eigenvalue problems. A Fortran 90 implementation for symmetric eigenvalue problems and another one in C for Hermitian eigenvalue problems are available with a BSD-like license.

Selected Publications
* Kesheng Wu, Arie Shoshani, and Kurt Stockinger. Analyses of Multi-Level and Multi-Component Compressed Bitmap Indexes. ACM Transactions on Database Systems v35, Article 2, 2010. DOI 10.1145/1670243.1670245
[Abstract] [Draft as LBNL-60891]
* Kesheng Wu, Ekow Otoo, and Kenji Suzuki. Optimizing two-pass connected-component labeling algorithms. Pattern Analysis & Applications, v12(2), pages 117 - 135. 2009. DOI 10.1007/s10044-008-0109-y
[Abstract] [Draft as LBNL-59102]
* Kesheng Wu, Ekow Otoo, and Arie Shoshani. Optimizing bitmap indices with efficient compression. ACM Transactions on Database Systems, v 31, pages 1-38, 2006. DOI 10.1145/1132863.1132864.
[Abstract] [Draft as LBNL-49626]
* Kesheng Wu, Ekow Otoo, and Arie Shoshani. On the Performance of Bitmap Indices for High Cardinality Attributes. VLDB 2004, pages 24 - 35.
[Abstract] [Draft as LBNL-54673]
* Kesheng Wu and Horst Simon. Thick-restart Lanczos method for large symmetric eigenvalue problems. SIAM Journal on Matrix Analysis and Applications, v 22, No. 2, pp. 602-616, 2001. DOI 10.1137/S0895479898334605
[Abstract] [Draft as LBNL-41412].
* Jim R. Chelikowsky, Norm Troullier, Kesheng Wu, and Yousef Saad. Combining a higher-order finite-difference method with ab initio pseudopotentials: application to diatomic molecules. Phys. Rev. B 50:11355-64, 1994. DOI: 10.1103/PhysRevB.50.11355
* Kesheng Wu, Robert Savit, and William Brock. Statistical tests for deterministic effects in broad band time series. Physica D: Nonlinear Phenomena 69(1-2): 172-188. 1993. DOI 10.1016/0167-2789(93)90188-7

*Publications listed elsewhere on the web:
[Google Scholar Profile] [Microsoft Academic Profile] [ACM Author Profile]
[Google Scholar] [ResearchGate] [DBLP]


Professional associations
ACM - Distinguished Scientist
IEEE - Senior Member
Current work place
University of California
Lawrence Berkeley National Laboratory, LBNL on youTube, UC events
Computational Research Division
High Performance Computing Research Department
Scientific Data Management Group
Earlier work
Scientific computing work at University of Minnesota
Related sites on database research
University of Minnesota Database group
UC Berkeley Database group
Stanford InfoLab
Related sites on scientific computing (eigenvalues in particular)
John Wu