E-mail: kwu
lbl.gov or
john.wuacm.orgMailstop 50B-3238, 1 Cyclotron Road, Berkeley, CA 94720, USA
lbl.gov or
john.wuacm.org
Analysis and management of large datasets
Parallel distributed software systems design and implementation
Component architecture for scientific software
Performance tuning for large distributed software
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.
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
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
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.
Kesheng Wu,
Ekow Otoo, and
Arie Shoshani.
On the Performance of Bitmap Indices for High Cardinality
Attributes.
VLDB 2004,
pages 24 - 35.
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
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] |
