[l/m 8/17/2006] Grand challenges and HPCC comp.parallel (22/28) FAQ
Eugene Miya
Last-modified: 16 Aug 2006
22 Grand challenges and HPCC
24 Suggested (required) readings
26 Dead computer architecture society
28 Dedications
2 Introduction and Table of Contents and justification
4 Comp.parallel news group history
6 parlib
8 comp.parallel group dynamics
10 Related news groups, archives and references
12
14
16 Problems posting?
18 Supercomputing and Crayisms
20 IBM and Amdahl
What is the list of "Grand Challenge" problems?
===============================================
Steve Stevenson:
See the blue book.
And people say that I am cynical.
[Sorry Steve, I have run out of tee-shirts.]
NOTE: This list is updated every year. The most recent version can be
obtained from the National Science Foundation through pu...@note.nsf.gov.
%Q Executive Office of the President, Office of Science and Technology Policy
%T The Federal High Performance Computing Program
%D Sept. 1989
%X Appendix A Summary, pages 49-50.
Prediction of weather, climate, and global change
Challenges in materials sciences
Semiconductor design
Superconductivity
Structural biology
Design of pharmaceutical drugs
Human genome
Quantum Chromodynamics
Astronomy
Challenges in Transportation
Vehicle Signature
Turbulence
Vehicle dynamics
Nuclear fusion
Efficiency of combustion systems
Enhanced oil and gas recovery
Computational ocean sciences
Speech
Vision
Undersea surveillance for ASW
What is ASW?
============
Anti-Submarine Warfare.
What constitutes a "Grand Challenge" problem?
=============================================
"A _grand_challenge_ is a fundamental problem in science or
engineering, with broad applications, whose solution would be
enabled by the application of high performance computing resources
that could become available in the near future.
Examples of grand challenges are:
(1) Computational fluid dynamics for
the design of hypersonic aircraft,
efficient automobile bodies, and
extremely quiet submarines,
for weather forecasting for
short and
long term effects,
efficient recovery of oil, and for many other applications;
(2) Electronic structure calculations for the design of new materials such as
chemical catalysts,
immunological agents, and
superconductors;
(3) Plasma dynamics for fusion energy technology and
for safe and efficient military technology;
(4) Calculations to understand the fundamental nature of matter,
including quantum chromodynamics and condensed matter theory;
(5) Symbolic computations including
speech recognition,
computer vision,
natural language understanding,
automated reasoning, and
tools for
design,
manufacturing,
and simulation of complex systems."
"A Research and Development Strategy for High Performance Computing"
Executive Office of the President
Office of Science and Technology Policy
November 20, 1987
The Top Ten most important algorithms
1. 1946: The Monte Carlo method (modeling probabilistic phenomena)
2. 1947: The Simplex method (linear optimization)
3. 1950: The Krylov subspace iteration method (fast linear solvers and
Eigensolvers)
4. 1951: The Householder matrix decomposition (express a matrix as a
product of simpler matrices)
5. 1957: The FORTRAN compiler (liberated scientists and engineers from
programming in assembly language)
6. 1959-1961: The QR algorithm (compute many eigenvalues)
7. 1962: The Quicksort algorithm (put things in numerical or alphabetic
order fast)
8. 1965: The fast Fourier transform (reduce operation count in Fourier
series representation)
9. 1977: The integer relation detection algorithm (useful for
bifurcations and in quantum field theory)
10. 1987: The fast multipole algorithm for N-body problems
J. Dongarra and F. Sullivan, eds., The top 10 algorithms, Computing in
Science and Engineering, Vol. 2, No. 1, January/February, 2000.
Articles: comp.parallel
Administrative: eug...@cse.ucsc.edu.SNIP
Archive: http://groups.google.com/groups?hl=en&group=comp.parallel
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