1.5.2 Computational Grand Challenge Problems

In 1991, Congress passed the High Performance Computing Act of 1991 (Public Law 102-194), which authorized The Federal High Performance Computing and Communications (HPCC) Program.

A class of problems developed in conjunction with the HPCC Program was designated "Grand Challenge Problems"¹ by Dr. Ken Wilson of Cornell University, a physicist and Nobel laureate. Since then various committees and government agencies have added others to the original list. These problems were characterized as "fundamental problems in science and engineering that have broad economic and/or scientific impact and whose solution can be advanced by applying high performance computing techniques and resources.'' They address issues of great societal impact, such as biomedicine, the environment, economic competitiveness, and national security. Many of the original Grand Challenge Problems involved simulations that, at the time the Act was passed, could not be completed fast enough or with enough accuracy.

An obvious way to make simulations run faster on a computer is to design faster computers, but faster computers alone are not the solution. The design of the algorithms that run on the computer is equally important, if not more so. Inefficient algorithms can quickly cancel out faster computers. In fact, it can be argued that it is far better to have today's mathematics and yesterday's computer than to have yesterday's mathematics and today's computer.

Some of the "Grand Challenges" currently underway deal with climate modeling, convective turbulence and mixing in astrophysics, computational biology, geophysical databases, condensed matter physics, and binary black holes. They also address problems in areas such as flow modeling, quantum chromodynamics, ground water remediation, and contaminant containment. Details of a few of the Grand Challenge Problems follow.

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