= what I did this week =

looked into how to compute the RREF of big sparse to moderately dense matrices (especially over GF(2)):

 * learned that this is a hard problem
 * looked into Macaulay F4 implementation, because they seem to do sparse elimination. got excited/depressed about its speed for Cyclic14 over GF(2) at a certain point, then found out that implementation is buggy and generated incorrect results
 * paired down code for structured Gaussian elimination, writing wrappers for this
 * at a certain point was not sure whether it would be easier to write wrappers or rewrite the code in Python/Cython
 * compressed matrix representations (deflate() each row): didn't get very far with that, deflate() generates a significant performance impact.
 * need more experimental data of matrices that I am really interested in: generating them