Grand Challenge problem

A Grand Challenge Problem is a general category of unsolved problems. The definition of a Grand Challenge problem has a certain degree of inherent subjectivity surrounding what is, or is not, a Grand Challenge. A Grand Challenge problem exhibits at least the following characteristics:

1. The problem is demonstrably hard to solve, requiring several orders-of-magnitude improvement in the capability required to solve it.
2. The problem can not be unsolvable. If it provably cannot be solved, then it can't be a Grand Challenge. Ideally, quantifiable measures that indicate progress toward a solution are also definable.
3. The solution to a Grand Challenge problem must have a significant economical and/or social impact.

Another, more simple definition is:

A grand challenge problem is one that cannot be solved in a reasonable amount of time with today's computers.

Fundamental scientific problems currently being explored generate increasingly complex data, require more realistic simulations of the processes under study, and demand greater and more intricate visualizations of the results. These problems often require numerous large-scale calculations and collaborations between people with multiple disciplines and locations.

The following are some examples of Grand Challenge problems:

• Applied Fluid Dynamics
• Meso- to Macro-Scale Environmental Modeling
• Ecosystem Simulations
• Biomedical Imaging and Biomechanics
• Molecular Biology
• Molecular Design and Process Optimization
• Cognition
• Fundamental Computational Sciences
• Grand-Challenge-Scale Applications
• Nuclear power and weapons simulations

See also

• Parallel computing

References

• Kranzlmüller, Dieter, , GUP Linz, Joh. Kepler University Linz, Austria (September 2000).
• NASA ESS (Earth and Space Sciences) project, , NASA High Performance Computing and Communications (HPCC) Program, JPL's High Performance Computing Group, (1998).
• San Diego Supercomputer Center (SDSC), , University of California, San Diego, (1999).