Computational Science & Engineering meeting national needs Steven F. Ashby SIAG-CSE Chair March 24, 2003

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Transcript Computational Science & Engineering meeting national needs Steven F. Ashby SIAG-CSE Chair March 24, 2003

Computational Science & Engineering
meeting national needs
Steven F. Ashby
SIAG-CSE Chair
March 24, 2003
Computational science challenges arise
in a variety of applications

Computational science is
emerging as its own
discipline
Turbulence

Fusion
Simulation is becoming a
peer to theory and
experiment in the process
of scientific discovery
Materials

Integration is the key
— domain science expert
— applied mathematician
— computer scientist
Biology
Lasers
Environment
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Computational
Applied Math
Domain Science
=
+
Science
Computer Science
Engineering
Applied Math
and CS
Computational scientists
bring applied mathematics
and computer science
capabilities to bear on
challenging problems in
science and engineering
Science and
Engineering
Applications
Biology
Physics
Chemistry
Engineering
Environmental
Math
sparse linear solvers
nonlinear equations
differential eqns
multilevel methods
AMR techniques
optimization
eigenproblems
CS
data management
data mining
visualization
program’g models
languages, OS
compilers, debuggers
architectural issues
Computational Science & Engineering is a team effort!
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Our focus has been on solving PDEs on
increasingly finer meshes

Traditional supercomputing applications involve the
solution of a PDE on a computational grid
— computational fluid dynamics
— oil reservoir and groundwater management
— stockpile stewardship
— ICF and MFE applications

Bigger machines and smarter algorithms have
allowed more realistic simulations
— Moore’s Law and massively parallel computers
have provided unprecedented computing power
— scalable algorithms enable large-scale
simulations
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Imagine the future of computational
science by looking at today’s challenges

Consider the process of scientific simulation
— software development
— problem definition and simulation setup
— data analysis and understanding

There has been no equivalent of Moore’s Law for how
we develop our software

Increasingly complex simulations often require
months to set up and months to analyze the results
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Investment needed in several areas
(illustrative, not exhaustive)

Multi-level methods for multi-scale problems

Rapid problem setup tools (mesh generation and
discretization methods for complex geometries)

Flexible software frameworks and interoperable s/w
components for rapid application development

Computer architectures & performance optimization

Information exploitation (data management, image
analysis, info/data visualization, data mining)

Systems engineering to integrate simulation, sensors,
and info analysis into a decision support capability

Discrete simulation (scenario planning)

Validation and Verification (coupling to experiments)
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This workshop is about shaping CS&E
programs for federal funding agencies

We should focus on how CSE can benefit the nation
— enhancing national & homeland security
— promoting economic vitality and energy security
— improving human health

We need to emphasize the multi-disciplinary nature of
CS&E and its track record in delivering!
— distinguish ourselves from constituent disciplines
— need to do a better job of getting the word out!

Think big: $250M, multi-agency initiative!
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We have long-time and natural partners in
the federal government

DOE has been long-time leader in CS&E
— ASCI re-invigorated supercomputing
— Office of Science is championing the cause with
its successful SciDAC initiative

NSF has long invested in IT and CS, and is beginning
to think more about CS&E

DHS has pressing needs for help in simulation and
information fusion

NIH should be a bigger player than it is, but there are
serious cultural obstacles
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SIAM Activity Group promotes
Computational Science & Engineering

SIAG-CSE established in Dec 2000 and already is
largest SIAG with 800 members

Foster collaborations among applied mathematicians,
computer scientists, domain scientists and engineers

Promote and facilitate Computational Science and
Engineering as an academic discipline

Promote simulation as a peer to theory and
experiment in the process of scientific discovery

Has sponsored two successful conferences

http://www.siam.org/siags/siagcse.htm
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