A key goal of the HPCC Program is to demonstrate the use of high performance computing and communications technologies to discover new knowledge and illustrate new capabilities that were not possible with earlier technologies. The Program has conducted R&D in Grand Challenge applications, which are fundamental problems in science and engineering with broad economic and scientific impact whose solution can be advanced by applying HPCC technologies. In addition to scientific importance, selection criteria included potential for cost sharing with sources directly concerned with the specific applications and the potential for leveraging across disciplines.
A common feature of many of these Grand Challenges is that they involve simulation. In part because of HPCC technologies, simulation has become recognized as the third paradigm of science, the first two being experimentation and theory. In some cases it is the only approach available for further advancing knowledge -- experiments may not be possible due to size (very big or very small), speed (very fast or very slow), distance (very far away), dangers to health and safety (toxic or explosive), or the economics of conducting the experiments. In simulations, mathematical models of physical phenomena are translated into computer software that specifies how calculations are performed using input data that may include both experimental data and estimated values of unknown parameters in the mathematical models. By repeatedly running the software using different data and different parameter values, an understanding of the phenomenon of interest emerges. The realism of these simulations and the speed with which they are produced affect the accuracy of this understanding and its usefulness in predicting change.
Due to limitations such as speed and memory in computing systems available at the beginning of the HPCC Program, many simulations could not be completed with sufficient accuracy and timeliness to be of interest. Through efforts requiring collaboration among computer scientists, mathematicians, computational scientists, and subject matter specialists, these limitations are being removed. In particular over the past year many Grand Challenge teams have reported advances that have been the result of faster run times, larger memory, higher resolution and more realistic modeling. Several dozen Grand Challenge applications projects and Grand- Challenge-scale applications are now described. Many of these involve multi-agency cooperation and support, In particular, all of the NSF Grand Challenges described are also supported by ARPA.