Capability Machines Panel
Panel Chair: Dr.
Horst Simon, Assoc. Lab Director for CS at Berkeley Lab, USA
The recent NRC study on the "Future of Supercomputing" defines
capability computing as "enabling the solution of problems that
cannot be otherwise solved in reasonable amount of time. ... Capability
computing also enables the solution of problems with real-time constraints." In
my presentation I will describe the work load at NERSC, and how NERSC
addresses the requirements of the Office of Science user community.
While NERSC serves a large number of users (2400), I will argue that
nevertheless provides capability computing. I will also discuss metrics
that NERSC is using to assure that we meet capability requirements.
Questions for the Panelists:
(From the NRC report): "Two commonly used measures of
the overall productivity of high end computing platforms are capacity
The largest supercomputers are used for capability or turnaround computing
where the maximum processing power is applied to a single problem. The
goal is to solve a larger problem, or to solve a single problem in a
shorter period of time. Capability computing enables the solution of
problems that cannot otherwise be solved in a reasonable period of time
(for example, by moving from a two-dimensional to a three-dimensional
simulation, using finer grids, or using more realistic models). Capability
computing also enables the solution of problems with real-time constraints
(e.g., intelligence processing and analysis). The main figure of merit
is time to solution. Smaller or cheaper systems are used for capacity
computing, where smaller problems are solved. Capacity computing can
be used to enable parametric studies or to explore design alternatives;
it is often needed to prepare for more expensive runs on capability systems.
Capacity systems will often run several jobs simultaneously. The main
figure of merit is sustained performance per unit cost. There is often
a trade-off between the two figures of merit, as further reduction in
time to solution is achieved at the expense of increased cost per solution;
different platforms exhibit different trade-offs. Capability systems
are designed to offer the best possible capability, even at the expense
of increased cost per sustained performance, while capacity systems are
designed to offer a less aggressive reduction in time to solution but
at a lower cost per sustained performance."
With this in mind, please answer the following questions/address the
following topics in your 10 minute presentation:
- Briefly describe the capability resources at your site.
- By example
describe one or two applications, where your unique capability platform
was critical in providing a solution.
- Do you agree with the above distinction
between capability and capacity? If not, how would you define these
- Is the distinction between capability and capacity useful?
- What metrics
do you use to measure "capability"?
- How could we as a community
improve these metrics?
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