Accuracy and Stability of Numerical Algorithms
Accuracy and Stability of Numerical Algorithms
Teraflops and Other False Goals
IEEE Parallel & Distributed Technology: Systems & Technology
The Magic Words are Squeamish Ossifrage
ASIACRYPT '94 Proceedings of the 4th International Conference on the Theory and Applications of Cryptology: Advances in Cryptology
Computational Verifiability and Feasibility of the ASCI Program
IEEE Computational Science & Engineering
A probabilistic scheduling heuristic for computational grids
Multiagent and Grid Systems
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The U.S. high-performance computing community still uses the term "Grand Challenge" for a variety of difficult problems in computational science. Though it was primarily a means of communicating computing goals to nonpractitioners, it also serves the useful purpose of letting practitioners focus on defining goals more carefully. For purposes of Grand Challenge computing, it is essential to have precise goals, and a way of measuring progress toward those goals. Many Grand Challenges have neither. A particularly common error is to measure the size of a computing problem with some integer "N" that represents the number of grid points or the number of particles or some other count of a discrete quantity. Another common error is to use measures of hardware activity, such as floating point operations per second, as a valid goal for an application programmer. This paper presents an approach to measuring the progress of physical simulations that shows promise for putting computational efforts on firmer scientific ground.