The Potential Impact of High-End Capability Computing on Four Illustrative Fields of Science and Engineering (2008) / Chapter Skim
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6 Numerical and Algorithmic Characteristics of HECC That Will Be Required by the Selected Fields
6 Numerical and Algorithmic Characteristics of HECC That Will Be Required by the Selected Fields
Pages 105-120
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From page 105... ...
and (f) of the charge: "Identify the numerical and algorithmic characteristics of the high-end capability computing requirements needed to address the scientific questions and technological problems identified in [Chapters 2-5]
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From page 106... ...
Thus scalable parallel I/O software would be extremely critical in these situations in the long term. In all of the HECC-dependent areas of astrophysics reviewed in Chapter 2, there is a strong science case to use the increase in computational capability expected over the next 10 years to increase model fidelity.
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From page 107... ...
The specific problems stemming from massive amounts of data are discussed in Chapter 2. Software Infrastructure There are three drivers for the development of software infrastructure for astrophysics in the long term.
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From page 108... ...
NUMERICAL AND ALGORITHMIC CHARACTERISTICS OF HECC FOR THE ATMOSPHERIC SCIENCES In the atmospheric sciences, the requirements, opportunities, and challenges divide roughly into near term (1-5 years) and long term (5-10 years)
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From page 109... ...
This process will incorporate new ideas being developed in the multiscale mathematics community that will provide techniques for using such small-scale simulations to inform models at the larger scales. Algorithms One of the principal drivers of algorithm development in atmospheric models is the need for substantial increases in spatial resolution, both in climate modeling and NWP.
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From page 110... ...
Software Infrastructure The comments about software infrastructure for the long-term needs of astrophysics apply equally well to the atmospheric sciences. But the atmospheric sciences face some additional issues because some of their computational products are used operationally for NWP.
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From page 111... ...
In the longer term -- once the foundations for simulation as a mode of inquiry become well e stablished -- the numerical, algorithmic, and other related infrastructure requirements of evolutionary biology will be very similar to those of astrophysics and the atmospheric sciences. A particularly exciting longer-term impact of the use of HECC for evolutionary biology is that the dynamic interplay of ecological genetics, evolutionary genetics, and population genetics will be studied, whereas today ecological theory and evolutionary theory have most often been studied in isolation, as noted in Chapter 4.
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From page 112... ...
Given that some 80 percent of the chemical separations industry essentially relies on understanding phase equilibria -- whether explicitly formulated as a thermal-based distillation problem or as the context for developing MSA materials -- the current capabilities of computational chemistry must be significantly extended to address Major Challenges 1 and 2 in Chapter 5. Computational chemistry includes calculations at the molecular scale with algorithms based on quantum chemical theories and classical analogs that evaluate the energetics of molecular conformations, as well as statistical mechanical methods that sample those conformations consistent with thermodynamic variables such as temperature and pressure.
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From page 113... ...
Significant algorithmic improvements over the last 5 years allow for MP2 calculations of 40-50 atom systems on a single processor; recent modestly scaling parallel algorithms allow for MP2 calculations on larger chemical systems of up to a few hundred atoms. Computational hardware improvements would allow for the MP2 calculation of much larger fragments and model compounds, which would reduce the error in transforming the quantum mechanical data into parameters for empirical, classical potential energy surfaces of the chemical separations materials of interest.
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From page 114... ...
CATEGORIZATION OF NUMERICAL AND ALGORITHMIC CHARACTERISTICS OF HECC NEEDED IN THE FOUR SELECTED FIELDS Models A common thread emerging from this study of four fields is the need to develop models whose detailed mathematical structure is still not completely specified, much less understood. In astrophysics and the atmospheric sciences, the need for new models arises from the attempt to represent complex combinations of physical processes and the effect of multiple scales in a setting where many of the constituent processes (fluid dynamics, radiation, particle dynamics)
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From page 115... ...
The construction of such methods, particularly in conjunction with the approaches to stiff timescales, described above, will require a deep understanding of the well-posedness of the problems being solved as initialvalue or boundary-value problems in order to obtain matching conditions across spatial regions with different resolutions. Finally, the need for high-performance particle methods arises in both astrophysics and chemical separations.
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From page 116... ...
More generally, the prospect of radical changes in all aspects of the HECC enterprise -- hardware, programming models, algorithms, and applications -- makes it essential that the computational science community, including both applications developers and library developers, work closely with the computer scientists who are designing the hardware and software for HECC systems. CROSSCUTTING CHALLENGES FROM MASSIVE AMOUNTS OF DATA Of the four fields examined in this study, three -- astrophysics, atmospheric science, and evolutionary biology -- can be characterized as very data intensive.
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From page 117... ...
One of the most challenging needs for astrophysics and atmospheric science is the ability to share observational data and simulation data along with derived data sets and information. The atmospheric sciences are further along in providing common formats and sharing of data, but a tremendous amount of work remains to be done.
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From page 118... ...
The atmospheric science community has evolved in the direction of well-supported community codes largely because agencies and institutions recognized that computing for both research and operations was increasingly converging toward shared goals and strategies. One consequence is that the atmospheric sciences field has offered proportionally greater opportunities for training workshops, internships, and fellowships in the computational sciences than the other three fields.
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From page 119... ...
Advances in chemical separations rely heavily on compute-bound algorithms of electronic structure theory solved by advanced linear algebra techniques, as well as on advanced sampling methods founded on statistical mechanics, to do large particle simulations of materials at relevant thermodynamic state points. Chemistry and chemical engineering departments at universities traditionally employ theoretical/ computational scientists who focus broadly on materials science applications but less on chemical separations problems, which are more strongly centered in the industrial sector.
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From page 120... ...
The primary challenge is to define a career track for a computational generalist who can move smoothly into and out of science domains as the need arises for his or her expertise and have those contributions integrated into a departmental home that recognizes their value. Astrophysics, atmospheric sciences, and chemical separations are most ready for the first model -- direct integration of computational science into the core discipline curriculum -- while evolutionary biology has received the attention of statisticians, physicists, and computer scientists to develop something closer to the second model.
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