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Post notes the exponential growth in processor speed and the advent of massive parallelization, resulting in increased computing power by thirteen orders of magnitude since 1945, but comments "However, the complicated architectures of these new platforms have made programming more difficult" and "Furthermore, much of the improved predictive power has been achieved by increasing the complexity of the application models and algorithms." The latter, he said, "has raised the level of the challenges associated with developing and using the large, complex computer codes." He said, "Many, if not most application codes achieve only a small fraction of the potential peak performance."
Post also said, "With regard to the Prediction Challenge, computational science does not have the predictive reliability of traditional methodologies such as theory, experiment and engineering design. The results of many major computer applications are often wrong or are misinterpreted, sometimes with disastrous consequences."
"Computational science must mature as a field if it is to become a reliable methodology for addressing important problems," he said.
For further information, or to request a copy of his paper, contact Doug at email@example.com