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What do we currently mean by Computational Science?

What do we currently mean by Computational Science?. Traditionally focuses on the “hard sciences” and engineering Physics, Chemistry, Mechanics, Aerospace, etc. Mesh-based calculations, direct numerical simulations, optimization, etc. – modeling the scientific phenomenon directly

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What do we currently mean by Computational Science?

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  1. What do we currently mean by Computational Science? • Traditionally focuses on the “hard sciences” and engineering • Physics, Chemistry, Mechanics, Aerospace, etc. • Mesh-based calculations, direct numerical simulations, optimization, etc. – modeling the scientific phenomenon directly • Used for verification of experiments, verification of theory, and, increasingly, predictive capabilities • Associated research: numerical algorithms, “big” hardware (computing, storage, networking) • Requires teams of experts – no single researcher can do it all

  2. One Example: DOE SciDAC Program • A program that works • “I’ve never been so happy as a computational scientist”, Tony Mezzacappa, TSI, March 11, 2003 • Targets specific Office of Science applications • Fusion, Accelerator Design, Basic Energy Sciences, Climate, Astrophysics, etc. • Unites these application scientists with ISICS • 3 Applied Mathematics (TOPS, APDEC, TSTT) • 4 Computer Science (CCA, PERC, Scalable Systems, Data Management) • ISICs are charged with collaborating with application teams • What’s missing from this program? How can it be improved? • The obvious: more applications, more CS, more math • Tighter ties with computer architecture development…. What else?

  3. Research Themes What new directions can/should be explored? • CS&E digging more deeply into the traditional areas • Multiscale modeling, hybrid solution techniques, etc. • CS&E moving into “nontraditional” areas • Biological sciences, economics, medicine, computational finance, etc. • Some traditional techniques, but also data mining, statistics,… • It’s not always about big hardware • What about… • English, Law, History, Archeology,…? • Almost no exposure in these areas – How can this be rectified? What can be accomplished if we turn our attention in these areas?

  4. Supporting CS&E What has worked? How do we go forward? • Large, goal-based initiatives have worked • Requires • Advances in applications, mathematics, and computer science • Integration of the three areas • An adequate reward system for those interactions • Examples • Grand Challenges, DOE SciDAC program • This is much easier at the labs than universities..

  5. Education Is the educational system “on track” for CS&E? • Many institutions are trying to understand where CS&E fits within their departmental structures • Computational science still traditionally done in the “discipline” departments • It’s difficult to find new hires that have been trained in all three aspects of computational science • Very few educational programs take a truly interdisciplinary tact • Typically 1 or 2 aspects considered • Of course, there are exceptions, e.g., TICAM, DOE CSGF • How do we increase the number of programs that are truly interdisciplinary? Can we? Should we? • How can we help stretch departmental budgets to accommodate cross-cutting curricula? What infrastructure is/can be provided at the national level from NSF or SIAM? • How do we encourage the exploration of new disciplines?

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