of code that can take full advantage of multicore processors. Multicore parallelism is unfamiliar to many commercial software developers, and it also requires different sorts of parallel algorithm development.
Conclusion 6. All four fields will need new, well-posed mathematical models to enable HECC approaches to their major challenges. Astrophysics and the atmospheric sciences share two needs: one for new ways to handle stiff differential equations and one for continuing advances in multiresolution and adaptive discretization methods. Astrophysics and chemical separations also share two needs: one for accurate and efficient methods for evaluating long-range potentials that scale to large numbers of particles and processors and one for stiff integration methods for large systems of particles.
In addition, it is clear to the committee that the management, analysis, and mining of data present an increasingly critical and crosscutting algorithmic challenge. Enormous sets of input data, such as those from satellites and telescopes, require HECC to digest data and elicit insights.
Conclusion 7. To capitalize on HECC’s promise for overcoming the major challenges in many fields, there is a need for students in those fields, graduate and undergraduate, who can contribute to HECC-enabled research and for more researchers with strong skills in HECC.
The committee foresees a growing need for computational scientists and engineers who can work with mathematicians and computer scientists to develop next-generation HECC software. Chapters 4, 5, and 6 explicitly mention a need for the more widespread teaching of scientific computing. Specifying an optimal career path for people who are able to straddle HECC and a traditional discipline is problematic, especially in academia. What is needed is a path that encompasses both a service role (HECC consulting within their field and to computer scientists) and opportunities to conduct their own research.
Even though the four fields selected for this study are disparate, the committee was able to develop major challenges for each and then determine which of those challenges are critically dependent on HECC. The following are suggestions for evaluating the potential impacts of HECC in other fields:
It is necessary to build on the existing consensus about a field’s current frontiers or major challenges. Developing from scratch a consensus picture of the frontier and of the major challenges that define promising directions for extending that frontier is in itself a sizable task.
It is important to determine which major challenges for the field are critically dependent on HECC. While it is easy to spot opportunities for applying HECC to gain advantage, that is not the same as identifying the challenges whose progress will be impeded without the use of appropriate HECC.
All the infrastructure components needed to apply HECC to the challenges that depend on it must be identified, and the community must develop a clear understanding of the resources needed to complete the infrastructure. Merely giving a field access to supercomputers is no guarantee that the field’s scientific progress will be enabled or accelerated.