[IEEE-bhpjobs] Triangle Computer Science Distinguished Lecturer Series

[walter heger]

130A North Building, Duke University (telecast from NCSU)
4:00 p.m. - 5:00 p.m.
Monday, April 4, 2005


An Overview of High Performance Computing and Self Adapting
Numerical Software

Jack Dongarra

Abstract

In this talk we will look at how High Performance computing
has changed over the last 10-year and look toward the
future in terms of trends. A new generation of software
libraries and algorithms are needed for the effective
and reliable use of (wide area) dynamic, distributed
and parallel environments. Some of the software and
algorithm challenges have already been encountered, such as
management of communication and memory hierarchies through
a combination of compile--time and run--time techniques,
but the increased scale of computation, depth of memory
hierarchies, range of latencies, and increased run--time
environment variability will make these problems much
harder.

Along these lines we will discuss work on the development
of parameterizable and annotatable software libraries
in the linear algebra area that will permit performance
tuning for a broad range of architectures. Self Adapting
Numerical Software (SANS) is a software effort that will
automatically generate highly optimized numerical kernels
for our high performance computers.


Biography

Jack Dongarra received a Bachelor of Science in Mathematics
from Chicago State University in 1972 and a Master of
Science in Computer Science from the Illinois Institute
of Technology in 1973. He received his Ph.D. in Applied
Mathematics from the University of New Mexico in 1980. He
worked at the Argonne National Laboratory until 1989,
becoming a senior scientist. He now holds an appointment
as University Distinguished Professor of Computer Science
in the Computer Science Department at the University of
Tennessee, has the position of a Distinguished Research
Staff member in the Computer Science and Mathematics
Division at Oak Ridge National Laboratory (ORNL), and an
Adjunct Professor in the Computer Science Department at
Rice University.

He specializes in numerical algorithms in linear algebra,
parallel computing, the use of advanced-computer
architectures, programming methodology, and tools
for parallel computers. His research includes the
development, testing and documentation of high quality
mathematical software. He has contributed to the design
and implementation of the following open source software
packages and systems: EISPACK, LINPACK, the BLAS, LAPACK,
ScaLAPACK, Netlib, PVM, MPI, NetSolve, Top500, ATLAS,
and PAPI. He has published approximately 200 articles,
papers, reports and technical memoranda and he is coauthor
of several books. He is a Fellow of the AAAS, ACM, and the
IEEE and a member of the National Academy of Engineering.


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Multimedia at Duke
Jessica Mitchell
D106 Levine Science Research Center, Duke University
11:45 a.m. - 12:45 p.m.
Friday, April 8, 2005
 --------------------------------
Duke Computer Science Colloquium
D106 Levine Science Research Center, Duke University
11:45 a.m. - 12:45 p.m.
Monday, April 11, 2005

Bruce Donald

Algorithmic Challenges in Structural Molecular Biology
and Proteomics

Abstract

Some of the most challenging and influential opportunities
for Physical Geometric Algorithms (PGA) arise in developing
and applying information technology to understand the
molecular machinery of the cell. Our recent work (and
work by others) shows that many PGA techniques may be
fruitfully applied to the challenges of computational
molecular biology. PGA research may lead to computer
systems and algorithms that are useful in structural
molecular biology, proteomics, and rational drug design.

Concomitantly, a wealth of interesting computational
problems arise in proposed methods for discovering
new pharmaceuticals. In this talk, I'll discuss some
recent results from my lab, including new algorithms
for interpreting X-ray crystallography and NMR (nuclear
magnetic resonance) data, disease classification using mass
spectrometry of human serum, and protein redesign. Our
algorithms have recently been used, respectively, to
reveal the enzymatic architecture of organisms high
on the CDC bioterrorism watch-list, for probabilistic
cancer classification from human peripheral blood, and to
redesign an antibiotic-producing enzyme to bind a novel
substrate. I'll overview these projects, and survey some
of the algorithmic and computational challenges.

Biography

Bruce Donald is the Joan P. and Edward J. Foley Jr
1933 Professor in the Computer Science Department
at Dartmouth. He holds a joint appointment in the
Department of Chemistry and the Department of Biological
Sciences. From 1987-1998, Donald was a professor in the
the Cornell University Computer Science Department, with
a joint appointment in Applied Mathematics. He received
a B.A. from Yale University, and a Ph.D. from MIT. Donald
has worked in research, visiting, and faculty positions at
Harvard, Stanford, Interval Research Corporation, and MIT.

Donald has been a National Science Foundation Presidential
Young Investigator. He has worked in in several research
areas, including Robotics, Microelectromechanical Systems
(MEMS), Computational Biology, Graphics, and Geometric
Algorithms. Donald's latest research interest is in
computational structural biology and drug design. He
was awarded a Guggenheim Fellowship for his work on
algorithms for structural proteomics. Research in the
Donald laboratory is funded by the National Institutes
of Health under the auspices of the National Institute of
General Medical Sciences Protein Structure
Initiative.---------------------------------http://www.cs.duke.edu/dept_info
/colloquia/