Difference between revisions of "Discussion of: DOE/NSF Workshop on Correctness in Scientific Computing"
(Created page with "David: Bottom of Page 5: "The overall approach taken to achieve end-to-end correctness will typically involve the use of uncertainty quantification (e.g., to account for nois...") |
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| − | Bottom of | + | Bottom of page 5: "The overall approach taken to achieve end-to-end correctness will typically involve the |
use of uncertainty quantification (e.g., to account for noisy data), checks of agreement with real-world | use of uncertainty quantification (e.g., to account for noisy data), checks of agreement with real-world | ||
observations (e.g., pointwise validation against real-world measurements), and statistical methods (e.g., | observations (e.g., pointwise validation against real-world measurements), and statistical methods (e.g., | ||
similar to those used to provide projections for hurricane trajectories)." | similar to those used to provide projections for hurricane trajectories)." | ||
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| + | Top of page 7: "The opportunity costs of scientific computing software bugs can be arbitrarily high. If a bug surfaces during an experiment that cannot be repeated (e.g., processing a rare natural phenomenon), the world community | ||
| + | stands to lose. This is one reason why we absolutely must have hardened and trustworthy components at | ||
| + | our disposal. Unfortunately, practical experience (e.g., inability to handle “difficult matrices [132]”) suggests | ||
| + | that we are really not prepared in this manner." | ||
Revision as of 14:24, 17 January 2024
David:
Bottom of page 5: "The overall approach taken to achieve end-to-end correctness will typically involve the use of uncertainty quantification (e.g., to account for noisy data), checks of agreement with real-world observations (e.g., pointwise validation against real-world measurements), and statistical methods (e.g., similar to those used to provide projections for hurricane trajectories)."
Top of page 7: "The opportunity costs of scientific computing software bugs can be arbitrarily high. If a bug surfaces during an experiment that cannot be repeated (e.g., processing a rare natural phenomenon), the world community stands to lose. This is one reason why we absolutely must have hardened and trustworthy components at our disposal. Unfortunately, practical experience (e.g., inability to handle “difficult matrices [132]”) suggests that we are really not prepared in this manner."