SciDAC 2005
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Opening Address at SciDAC 2005
Michael Strayer, SciDAC Program Director

Good morning. Welcome to SciDAC 2005 and San Francisco.

Ray Orbach had intended to give the opening address. However as the Secretary’s science advisor he is at this moment on his way to Moscow with the Secretary. Ray is a strong proponent and supporter of Scientific Computing and he sends his best wishes and his regrets. This morning I would like to share with you some of my views on SciDAC.

SciDAC is all about computational science and scientific discovery. In a large sense, computational science characterizes SciDAC and its intent is change. It transforms both our approach and our understanding of science. It opens new doors and crosses traditional boundaries while seeking discovery. In terms of 20th century methodologies, computational science may be said to be transformational.

There are a number of examples to this point. The first are the sciences that encompass climate modeling. The application of computational science has in essence created the field of climate modeling. This community is now international in scope and has provided precision results that are challenging our understanding of our environment.

A second example is that of lattice quantum chromodynamics. Lattice QCD, while adding precision and insight to our fundamental understanding of strong interaction dynamics, has transformed our approach to particle and nuclear science. The individual investigator approach has evolved to teams of scientists from different disciplines working side-by-side towards a common goal

SciDAC is also undergoing a transformation. This meeting is a prime example. Last year it was a small programmatic meeting tracking progress in SciDAC. This year, we have a major computational science meeting with a variety of disciplines and enabling technologies represented. SciDAC 2005 should position itself as a new corner stone for Computational Science and its impact on science.

As we look to the immediate future, FY 2006 will bring a new cycle to SciDAC. Most of the program elements of SciDAC will be re-competed in FY 2006. The re-competition will involve new instruments for computational science, new approaches for collaboration, as well as new disciplines. There will be new opportunities for virtual experiments in carbon sequestration, fusion, and nuclear power and nuclear waste, as well as collaborations with industry and virtual prototyping. New instruments of collaboration will include institutes and centers while summer schools, workshops and outreach will invite new talent and expertise.

One of the interesting things about science is that it never stands still. Computational science adds new dimensions to science and its practice. Disciplines of fusion, accelerator science and combustion are poised to blur the boundaries between pure and applied science. As we open the door into FY2006 we shall see a landscape of new scientific challenges: in biology, chemistry, materials, and astrophysics to name a few.

The enabling technologies of SciDAC have been transformational as drivers of change. Planning for major new software systems assumes a base line employing Common Component Architectures and this has become a household word for new software projects. While grid algorithms and mesh refinement software have transformed applications software, data management and visualization have transformed our understanding of science from data. The Gordon Bell prize, now seems to be dominated by computational science and solvers developed by TOPS ISIC.

The priorities of the Office of Science in the Department of Energy are clear. It’s 20 year facilities plan is driven by new science. High performance computing is placed amongst the highest two priorities. Moore’s law says that by the end of the next cycle of SciDAC we shall have petaflop computers. The challenges of peta scale computing are enormous. These and the associated computational science are the highest priorities for computing within the Office of Science. Our effort in Leadership Class computing is just a first step towards this goal.

Clearly, computational science at this scale will face enormous challenges and possibilities. Performance evaluation and prediction will be critical to unraveling the needed software technologies. We must not loose sight of our overarching goal – that of scientific discovery. Science does not stand still and the landscape of science discovery and computing holds immense promise. In this environment, I believe it is necessary to institute a system of science based performance metrics to help quantify our progress towards science goals and scientific computing.

As a final comment I would like to reaffirm that the shifting landscapes of science will force changes to our computational sciences, and leave you with the quote from Richard Hamming, “The purpose of computing is insight, not numbers.”

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