Foreword By Thomas Zacharia
Computation is becoming an equal partner with theory and experimentation in the advancement of science.
The Future of High-Performance Computing By Richard F. Sincovec
The World Wide Web is expected to give computational researchers enhanced capabilities for retrieving and visualizing data and for solving problems.
The Center for Computational Sciences: High-Performance Computing Comes to ORNL By Kenneth Kliewer
The CCS focuses on solving Grand Challenge problems by linking powerful parallel computers together and by developing parallel applications codes and algorithms.
Industrial-Strength Computing: ORNL's Computational Center for Industrial Innovation By Harvey Gray
CCII is helping researchers from U.S. industrial firms, government agencies, and universities harness parallel computing to solve complex industrial problems.
Scientific Visualization at ORNL By Ross Toedte and Dianne Wooten
Better insight into scientific phenomena is the goal of ORNL's Visualization Laboratory, which uses visualization and virtual reality techniques and the latest software and hardware.
Visualization and Virtual Environments Research By Raymond E. Flanery, Jr., Nancy W. Grady, Joel W. Reed, and Daniel R. Tufano
ORNL's Advanced Visualization Research Center has explored climate modeling, seismic modeling, melting simulations, data mining, and three-dimensional medical imaging.
Algorithms, Tools, and Software Aid Use of High-Performance Computers By Ed D'Azevedo, Jack Dongarra, Tom Dunigan, Al Geist, Chuck Romine, and Pat Worley
ORNL and the University of Tennessee are leaders in developing tools for using high-performance computers efficiently.
Software Components To Facilitate Application Development By Jack Dongarra, Noel Nachtigal, Esmond Ng, Barry Peyton, Bill Shelton, and David Walker
ORNL researchers have developed computationally efficient linear algebra packages that are portable across different computer architectures. These tools have led to fast simulations of use to materials scientists and the automotive and aerospace industries.
High-Performance Computing: Innovative Assistant to Science By James Arthur Kohl
An ORNL computational tool developed for scientists is CUMULVS, which helps them simulate experiments and change the parameters in midcourse to influence the results, saving time and money.
Computing the Genome By Edward Uberbacher
ORNL is helping to design and prepare to implement a new computational engine to rapidly analyze large-scale genomic sequences. The goal is to keep up with the flood of data from the Human Genome Project.
Developing a Grand Challenge Materials Application Code By William A. Shelton and G. Malcolm Stocks
Computational methods and parallel processors enable scientists to simulate magnetic and other properties of metallic alloys based on the electronic structure of thousands of atoms.
How Solids Melt: ORNL Simulations Support Theory By Mark Mostoller, Ted Kaplan, and Kun Chen
Using parallel computing, ORNL scientists obtained insights into how substances melt in two dimensions and confirmed that a phase between the solid and liquid phases exists.
Giant Magnetoresistance in Layered Magnetic Materials By Bill Butler, Xiaoguang Zhang, and Don Nicholson
By using advanced computational techniques, ORNL scientists are learning how and why electrical resistivity varies in thin layers of magnetic alloys. This understanding could lead to improved magnetic memory for computers and motion sensors for appliances.
Edge Dislocations in Silicon By Mark Mostoler, Ted Kaplan, and Matt Chisholm
Using parallel computing, ORNL scientists inferred that edge dislocations in silicon that have no dangling bonds and no segregated impurities may be electrically or optically active.
High-Performance Computing in Groundwater Modeling By Laura Toran, J. Gwo, G. Mahinthakumar, E. D'Azevedo, and C. Romine
Computationally intense models that describe concentrations and movements of specific contaminants in groundwater may be more effective than simple groundwater models in evaluating remediation options.
Analysis of Material Performance in Automotive Applications By Srdan Simunovic, Gustavo Aramayo, and Thomas Zacharia
Computer simulations of collisions involving vehicles made of materials lighter than steel offer a quicker, cheaper way to guide the design of future vehicles to make them safer as well as more efficient.
Optimization of MicrostructureProperty Relationship in Materials By Balasubramaniam Radhakrishnan, Gorti Sarma, and Thomas Zacharia
An ORNL computer model could be used to develop the optimum processing window for producing controlled texture in aluminum to minimize scrap from the manufacture of aluminum beverage cans.
Computational Engine Modeling By Osman Yasar
ORNL has adapted an engine combustion code for use on parallel computers, enabling faster designs of highly efficient and environmentally friendly cars.
From a Distance: Remote Operation of Research Equipment By Carolyn Krause
ORNL has received DOE 2000 funding to conduct experiments involving collaboration by electronic means among geographically separated researchers, including the remote operation of research equipment and development of electronic notebooks.
Crisis Management and Collaborative Computing: ORNL's Contributions By Kimberly Barnes, John Cobb, and Nenad Ivezic
ORNL researchers have been combining software engineering, computational science, and collaborative technologies to solve problems in enterprise management, disaster management, education, banking and finance, and engineering design and manufacturing.