Parallel and Distributed Computing LaboratoryDept. of Computer Science & Information Engineering
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Members:Wei-Jen Wang (Assistant Prof.,
Director) |
The members of the Parallel and Distributed Computing Laboratory (PaDiC Lab) focus on the research issues of parallel and distributed computing, including distributed programming and cloud/grid computing. We are also studying and working on the related issues of Internet applications, such as information hiding, system security, e-science, and e-learning. Our research interests include but are not limited to the following topics:
Large-scale distributed programming frameworks
Grid/Cloud computing
Scientific computing algorithms/frameworks
Parallel and distributed algorithms
Information hiding
Cloud Computing Environment (Grants
"NSC100-2218-E-008-005-" and "NSC99-2218-E-008-012-"
by NSC, Taiwan, and "Cloud Computing technologies & industry
development" by the Institute for Information Industry, Taiwan)
The purpose of this project is to
establish a secure and stable cloud computing environment that can
simultaneously host numerous users' applications. We currently focus
our attentions on system monitoring, large-scale data analysis, and integration
of cloud technologies.
Worldwide Computing
Environment ("NSC97-2221-E-008-046-" and "NSC98-2221-E008-080-" by NSC, Taiwan):
The purpose of this research is to turn the Internet into a unified, worldwide
computing environment, which harnesses under-loaded computing resources by the
technique of dynamic system reconfiguration in a peer-to-peer manner. Our
worldwide computing environment research uses the following toolkits: (1) Condor, (2) Ganglia, (3) Message Passing Interface, (4) Java Programming
Language, and (5) the Simple Actor Language, System, and
Architecture (SALSA) The
Worldwide Computing Laboratory
at Rensselaer Polytechnic Institute in the US is our major collaboration
partner in this project.
Information Hiding:
Information hiding is a technique for embedding secret data into cover media. Our
work focuses on reversible data hiding for VQ-based images and raw images.
Large-Scale Scientific Computing Application, System, and
Architecture in Astronomy:
PANoramic Survey Telescope And Rapid
Response System (Pan-STARRS) is a planned astronomical survey that will
conduct astrometry and photometry of 3/4 of the entire sky every night. The
major goal of Pan-STARRS is to detect potentially hazardous objects, in
particular the near-earth objects in the Solar System. PS1, essentially one
quarter of Pan-STARRS, is the prototype of the Pan-STARRS, and is also expected
to have significant contribution in many areas of astronomy research. Pan-STARRS
is currently operated by the
University of Hawaii, which has set up an international consortium comprised
of research groups in Germany, the USA, the United Kingdom, and Taiwan. The
observed data from PS1 will be about 2-3 Terabytes per night which takes a long
time to finish data analysis. Therefore advanced computing technology,
especially grid/p2p computing technology, is required to improve
performance. Furthermore, many astronomy applications may also utilize the data
from PS1 to do their own analysis, which means there exist many research
potentials for grid computing in this area. The PaDiC Lab is collaborating with the
Graduate Institute of Astronomy at National Central University, Taiwan, on
PS1 related research.
The information can be obtained at Wei-Jen Wang's publication list.
Jian-hao Chiou (Master Student, 98G), Sih-Liang Shen (Master Student, 98G), Ting-Yuan Song (Master Student, 98G), Cheng-Hui Wu (Master Student, 98G), An-Ching Huang (Master Student, 99G), Wei-Xiang Kang (Master Student, 99G), Sheng-Hao Liu (Master Student, 99G), Yen-Jan Chang (Master Student, 100G), Po-Min Jiang (Master Student, 100G), Jing-Ying Huang (Master Student, 100G)
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