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Monte Carlo Arithmetic: How to Gamble with Floating Point and Win
July/August 2000 (vol. 2 no. 4)
pp. 58-68
How sensitive to rounding errors are the results generated from a particular code running on a particular machine applied to a particular input? Monte Carlo arithmetic illustrates the potential for tools to support new kinds of a posteriori round-off error analysis.
Citation:
D. Stott Parker, Brad Pierce, Paul R. Eggert, "Monte Carlo Arithmetic: How to Gamble with Floating Point and Win," Computing in Science and Engineering, vol. 2, no. 4, pp. 58-68, July-Aug. 2000, doi:10.1109/5992.852391
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