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QD (Quad-Double) Approach to Robustness: msg#00027

gis.geos.devel

Subject: QD (Quad-Double) Approach to Robustness

In a conversation with Dale Lutz at GeoAlberta, he mentioned they had experimented with using the QD library (<http://crd.lbl.gov/~dhbailey/ mpdist/>) in some of their topology processing and found that it was exceptionally good at bypassing problems caused by reduced precision. Presumably this is because all the input data is at double precision, at most, so relative to the processing precision (quad) it is quite well behaved. The approach was so good that in a race between the old algorithms (double precision but with lots of tests and bobbing and weaving to catch special cases) and the new (quad precision, with no special cases at all, just naive algorithms) the qd won hands down. So the overhead of the math library on all cases was not higher than the overhead of finding and handling the special cases.

Something to look at!

P


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