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Yesterday I accidentally tried to invert a 200×200 matrix in GAUSS.
Today was the penultimate Macro lecture given by the dynamic adjunct. He'll be back in four weeks to take the last lecture of the course, but until then we've got Prof A. I don't think it's any skin off Prof A's nose if I confess to being slightly sad at the loss of the dynamic adjunct; as a lecturer, he's a hard act to match.
Since the start of the trimester (70 days) I've handed in seven assignments, an essay, and a test. I've got back three of the assignments and the test; the rest have disappeared into a black hole. On average, the items that have returned took 7 days to surface. On average, the ones that haven't returned are now 18 days old. (One of them is 42 days old.)
2 comments:
Weird that it would have a problem with a 200x200 matrix. That's only 40k elements, or 0.32 MB of data on a machine that presumably has 1000 MB or more of RAM and even 5 year old machines usually have more cache than that.
Even the most naive algorithm is only O(n^3) in floating point operations, and 200^3 is 8 million. The slowest machines you can buy today do at least 1000 million floating point ops a second.
GAUSS seems to have its own internal resource restrictions which are completely unrelated to the machine it's running on. In particular, it simply refuses to have anything to do with any vector of dimension < 1000. Won't manipulate it, won't store it, won't let you declare it (even if it's explicitly declared empty). I haven't yet established a corresponding limit for matrices; GAUSS had no trouble storing my 200 by 200, but exited with failure on trying to manipulate it.
I can't imagine why artificially restricted resources would be a desirable feature, particularly in an engine which is primarily designed for manipulating big arrays.
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