What every computer scientist should know about floating-point arithmetic
ACM Computing Surveys (CSUR)
Matrix computations (3rd ed.)
Applications of randomization to floating-point arithmetic and to linear systems solutions
Applications of randomization to floating-point arithmetic and to linear systems solutions
The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
Accuracy and Stability of Numerical Algorithms
Accuracy and Stability of Numerical Algorithms
Perturbing and evaluating numerical programs without recompilation: the wonglediff way
Software—Practice & Experience
Perturbing numerical calculations for statistical analysis of floating-point program (in)stability
Proceedings of the 19th international symposium on Software testing and analysis
A monte-carlo floating-point unit for self-validating arithmetic
Proceedings of the 19th ACM/SIGDA international symposium on Field programmable gate arrays
Towards the profiling of scientific software for accuracy
Proceedings of the 2011 Conference of the Center for Advanced Studies on Collaborative Research
Natural Computing: an international journal
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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.