computation

Efficient Computation Through Tuned Approximation

David Keyes, Professor, Applied Mathematics and Computational Sciences

Oct 23, 11:30 - 12:30

B9 L2 R2322 H1

computation approximation software

Numerical software is being reinvented to provide opportunities to tune dynamically the accuracy of computation to the requirements of the application, resulting in savings of memory, time, and energy. Floating point computation in science and engineering has a history of “oversolving” relative to expectations for many models. So often are real datatypes defaulted to double precision that GPUs did not gain wide acceptance until they provided in hardware operations not required in their original domain of graphics. However, computational science is now reverting to employ lower precision arithmetic where possible. Many matrix operations considered at a blockwise level allow for lower precision and many blocks can be approximated with low rank near equivalents.

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genomics Computer science computation epigenetics

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big data visual computing computation Computer science

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