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Welcome The Computational
Research Division (CRD) creates computational tools and techniques
that enable scientific breakthroughs, by conducting applied research
and development in computer science, computational science, and
applied mathematics. CRD consists of three departments:
The Biological Data Management
and Technology Center (BDMTC) serves as a source of expertise
in and provides support for data management and bioinformatics tool
development projects at the Joint Genome Institute (JGI), Life Sciences
and Physical Biosciences Divisions at LBNL, Biomedical Centers at
UCSF, and other similar organizations in the Bay Area. The Center
enables collaborating organizations to share experience, expertise,
technology, and results across projects, employing industry practices
in developing data management systems and bioinformatics tools,
while maintaining academic high standards for the underlying data
generation, interpretation, and analysis methods and algorithms.
The Distributed Systems
Department researches and develops software components that
allow scientists to address complex and large-scale computing and
data analysis problems in a distributed environment such as the
DOE Science Grid. Just as the World Wide Web and browser software
make millions of information sources easily available to your computer,
a distributed computing environment or Grid integrates computing,
data storage, and instrumentation systems that are managed by various
organizations in widespread locations so that they function and
appear to the user as one system.
The High Performance
Computing Research Department conducts research and development
in mathematical modeling, algorithmic design, software implementation,
and system architectures, and evaluates new and promising technologies.
They collaborate directly with scientists, in fields ranging from
materials sciences to climate modeling to astrophysics, to solve
computational and data management problems. They also create visualizations
to help scientists gain new physical insights and make the data
more comprehensible.
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