Thus, in this report, capability computing is interpreted as computing that enables some new science or engineering capability—an insight or means of investigation that had not previously been available. In that context, high-end capability computing is distinguished by its ability to enable science and engineering investigations that would otherwise be infeasible.

HECC is also distinguished by its nonroutine nature. As the term “capability computing” is normally used, this corresponds to computing investments that are more costly and risky than somewhat time-tested “capacity computing.” This report retains that distinction: HECC might require extra assistance—for example, to help overcome the frailties encountered with a first-time implementation of a new model or software—and entail more risk than more routine uses of computing. But the committee’s focus on increasing scientific and engineering capabilities means that it must interpret “computing investments” to include whatever is needed to develop those nonroutine computational capabilities. The goal is to advance the fields. Progress might be indicated by some measure of computational capability, but that measure is not necessarily just processing power.

Targeted investments might be needed to stimulate the development of some of the components of HECC infrastructure, and additional resources might be necessary to give researchers the ability to push the state of the art of computing in their discipline. These investments would be for the development of mathematical models, algorithms, software, hardware, facilities, training, and support—any and all of the foundations for progress that are unlikely to develop optimally without such investments given the career incentives that prevail in academe and the private sector. Given that the federal government has accepted this responsibility (see the section below on history), it is faced with a policy question: How much HECC infrastructure is needed, and of what kind? To answer this, the committee sought and analyzed information that would give it two kinds of understanding:

  1. An understanding of the mix of research topics that is desirable for the nation. Each field explicitly or implicitly determines this for itself through its review of competing research proposals and its sponsorship of forward-looking workshops and studies. Federal policy makers who define programs of research support and decide on funding levels are involved as well.

  2. An understanding of the degree to which nationally important challenges in science and engineering can best be met through HECC. Answering the question about what kind of infrastructure is needed requires an understanding of a field’s capacity for making use of HECC in practice, not just potential ways HECC could contribute to the field. In that spirit, this report considers “HECC infrastructure” very broadly, to encompass not just hardware and software but also training, incentives, support, and so on.

This report supplies information that is needed to gain the insights described in (1) and (2) above. It also suggests to policy makers a context for weighing the information and explains how to work through the issues for four disparate fields of science and engineering. The report does not, however, present enough detail to let policy makers compare the value to scientific progress of investments in HECC with that of investments in experimental or observational facilities. Such a comparison would require estimates of the cost of different options for meeting a particular research challenge (not across a field) and then weighing the likelihood that each option would bring the desired progress.

Computational science and engineering is a very broad subject, and this report cannot cover all of the factors that affect it. Among the topics not covered are the following, which the committee recognizes as important but which it could not address:



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