Grand Challenges

Grand Challenges are defined by the Federal High Performance Computing and Communications (HPCC) program as fundamental problems in science and engineering with broad economic and scientific impact, whose solutions require the application of high-performance computing.

The following is a list of "official" Grand Challenge applications that are sponsored by the various federal agencies that are part of the Federal HPCC program. The applications are divided into the following categories:


Computational Aerosciences Project
NASA - NASA Ames, NASA Langley and NASA Lewis
Accelerate the development and availability of high-performance computing technology that will be of use to the U.S. aerospace community, facilitate the adoption and use of this technology by the U.S. aerospace industry, and hasten the emergence of a viable commercial market for hardware and software vendors to exploit this lead.

High performance computational methods for coupled field problems and GAFD turbulence
NSF - Colorado, Minnesota, and the National Center for Atmospheric Research
Develop and implement algorithms and software on parallel computers for solving field problems in structural and fluid dynamics and studying highly turbulent flows which arise in geophysical and astrophysical fluid dynamics.

Computer Science

High performance computing for learning
NSF - MIT, Brown and Harvard
Develop, implement, and test new mathematical techniques, software, and hardware for high performance computers with the ultimate goal of getting computers to "see, move, and speak."

Parallel I/O methodologies for I/O-intensive Grand Challenge applications
NSF - Caltech and Illinois
Investigate and develop strategies for the efficient implementation of I/O intensive applications on a specially configured Intel Paragon computer. They will characterize I/O behavior and performance, define I/O models and methodologies, and develop, implement and test tools to support scientific applications with large I/O requirements.


Mathematical combustion modeling
Developing adaptive parallel algorithms for computational fluid dynamics and applying them to combustion models.

Numerical Tokamak project
DOE - Lawrence Livermore, Texas, UCLA, Oak Ridge, Princeton, NASA JPL, Cornell, Los Alamos, Caltech, National Energy Research Supercomputer Center
Develop and integrate particle and fluid plasma models on massively parallel machines as part of the multidisciplinary study of Tokamak fusion reactors.

Oil reservoir modeling
DOE - Texas A&M, Brookhaven, Oak Ridge, Rice, Stony Brook, South Carolina, and Princeton
Develop software for massively parallel computers that calculates fluid flow through permeable media. The project has a dual application, focusing on methods that solve modeling problems for petroleum reservoirs and for groundwater contamination.

Quantum chromodynamics calculations
DOE - Los Alamos
Developing lattice gauge theory algorithms on massively parallel machines for high energy physics and particle physics applications.

Environmental Monitoring and Prediction

Adaptive coordination of predictive models with experimental observations
NSF - Stanford and NASA Ames
Using a predictive computer model carrying out simulations in real time and a laboratory test bed, the team will investigate the potential for the interplay of the simulations and the experimental facility to estimate what data need to be gathered, as well as the location and resolution of this data, in order that accurate predictions of the future behavior of a complex nonlinear fluid system such as the atmosphere or the ocean can be made.

Computational chemistry
DOE - Argonne, Pacific Northwest Laboratory, Allied Signal, du Pont, Exxon, and Phillips
Develop new parallel algorithms, software, and portable tools for computational chemistry, and develop modeling systems for critical environmental problems and remediation methods.

Data analysis and knowledge discovery in geophysical databases
Demonstrate the applicability of information systems for geophysical databases to support cooperative research in earth-science projects.

Development of algorithms for climate models scalable to TeraFLOP performance
NASA - NASA Goddard
Develop a high-resolution global climate model capable of centuries-long calculations on massively parallel machines at teraFLOP speed.

Development of an Earth system model: atmosphere/ocean dynamics and tracers chemistry
NASA - UCLA, Princeton, Berkeley, Santa Barbara, JPL, Lawrence Livermore
Develop a model of the coupled global atmosphere-global ocean system, including chemical tracers that are found in, and may be exchanged between the atmosphere and the oceans. Use the model to study the general circulation of the coupled atmosphere-ocean system, the global geochemical carbon cycle, and the global chemistry of the troposphere and stratosphere.

A distributed computational system for large scale environmental modeling
NSF - Carnegie Mellon and MIT
Use high performance heterogeneous computing systems, advanced software environments, parallel architectures, and networks to develop algorithms for multiphase chemistry and aerosol dynamics and a distributed computing approach for simultaneous solution and sensitivity of environmental models.

Earthquake ground motion modeling in large basins
NSF - Carnegie Mellon, USC and the National University of Mexico
Develop new mathematical models and software tools to demonstrate the capability for predicting, by simulation on parallel computers, the ground motion of large basins during strong earthquakes, and use this capability to study the seismic response of the Greater Los Angeles Basin.

Four-dimensional data assimilation for massive Earth system data analysis
NASA - NASA Goddard, NASA JPL, Syracuse
The goal of data assimilation is the calculation of consistent, uniform, spatial and temporal representations of the Earth environment that can be used for scientific analysis and synthesis. This involves the collection of diverse Earth observational data sets, and the incorporation of these data into models of the ocean, land surface, and atmosphere, including chemical processes.

Global climate modeling
DOE - Los Alamos, Argonne, Oak Ridge
Numerical studies of the Earth's climate using general circulation models of the atmosphere and ocean.

Groundwater transport and remediation
DOE - Texas A&M, Brookhaven, Oak Ridge, Rice, Stony Brook, South Carolina, and Princeton
Develop software for massively parallel computers that calculates fluid flow through permeable media. The project has a dual application, focusing on methods that solve modeling problems for petroleum reservoirs and for groundwater contamination.

High performance computing for land cover dynamics
NSF - Maryland, New Hampshire, Indiana, and NASA Goddard
Develop techniques to support access and analysis of remotely sensed data stored on parallel disk systems and use those techniques to facilitate the study of global ecological responses to climate changes and human activity.

Massively parallel simulation of large scale, high resolution ecosystem models
NSF - Arizona
Establish new algorithms and implementations for massively parallel processing that integrate geographical information systems databases with cellular discrete-event methodology to express large scale realistic ecosystem models and visualize their simulated behavior. The focus will be on monitoring and predicting landscape and ecosystem changes for large geographic regions

Molecular Biology and Biomedical Imaging

Advanced computational approaches to biomolecular modeling and structure determination
NSF - Illinois, Duke, NYU, Yale, and Eli Lilly Corporation
Develop models and molecular dynamics algorithms for a widely used program for structural biology (X-PLOR) in order to advance the fundamental understanding of molecular biology and pharmacology.

Computational biomolecular design
NSF - Houston
Use emerging scalable parallel computers and software to develop and implement new methods for solving critical problems in biomolecular design.

Computational structural biology
DOE - Caltech, Argonne, University of Washington, and UCLA
Understanding the components of genomes and developing a parallel programming environment for structural biology.

High performance imaging in biological research
NSF - Carnegie Mellon and Pittsburgh
Use the latest technologies in light microscopy and reagent chemistry with advanced techniques for computerized image analysis, processing and display, implemented on high-performance computers to produce an automated, high speed, interactive tool that will make possible new kinds of basic biological research on living cells and tissues.

Understanding human joint mechanics through advanced computational models
NSF - Rensselaer Polytechnic and Columbia
Develop automated and adaptive three-dimensional finite element analysis and parallel solution strategies to describe nonlinear moving contact problems characteristic of the biomechanics of joints in the human musculoskeletal system using the actual anatomic geometries and the multiphasic properties of the tissues in the joint.

Product Design and Process Optimization

First-principles simulation of materials properties
DOE - Oak Ridge, Brookhaven, NASA Ames
Investigate new methods for performing large-scale, first-principles simulation of materials properties using a hierarchy of increasingly more accurate techniques that exploit the power of massively parallel computing systems.

High capacity atomic-level simulations for design of materials modeling
NSF - Caltech, Columbia and NASA JPL
Formulate and implement new methodologies for parallel computers to carry out high capacity atomic-level simulations for design of materials, and apply the resulting software to critical industrial materials problems.

Space Science

Black hole binaries: coalescence and gravitational radiation
NSF - Texas, Illinois, Syracuse, Pittsburgh, Penn State, Northwestern, North Carolina and Cornell
Create a computational toolkit to provide modular development tools to support the study of coalescence of astrophysical black holes and the gravitational radiation emitted via the numerical solution of Einstein's equations for gravitational fields.

Convective turbulence and mixing in astrophysics
NASA - Colorado, Michigan State, Chicago, Argonne, NCAR
Develop the next generation of multi-dimensional hydrodynamic codes for astrophysical simulations involving turbulent convection, based on the use of massively parallel machines.

Cosmology and accretion astrophysics
NASA - Los Alamos, Syracuse, Penn State, Caltech, Australian National University
Develop parallel, scalable particle codes (N-body, smoothed particle hydrodynamic (SPH), and hybrid) based on hierarchical tree data structures and use them to study astrophysical problems.

The formation of galaxies and large-scale structure
NSF - Princeton, Illinois, Pittsburgh, MIT, Indiana, San Diego
Explore different numerical algorithms, mesh adaptation strategies, programming models and new software technologies in order to obtain detailed numerical simulations that can help answer the question: "What is the origin of large-scale structure in the universe and how do galaxies form?"

Large scale structure and galaxy formation
NASA - University of Washington, University of Toronto
Develop the tools needed for high performance N-body simulations, and use these to test the "standard model" for the origin of galaxies and large-scale structure by accurately evolving it into its present highly nonlinear state.

Radio synthesis imaging
NSF - Illinois, Wisconsin, Maryland, Berkeley
Implement a prototype of the next generation of astronomical telescope systems - remotely located telescopes connected by high-speed networks to very high performance computers and on-line data archives.

Solar activity and heliospheric dynamics
NASA - Naval Research Laboratory, NASA Goddard
Develop parallel algorithms for solar and heliospheric modeling.