Hi Simon,

what would be a nice piece of work. Good luck and have fun ;-)

Please test the following if your implementation is ready: Try to use your 
Strassen implementation only with 1 step of recursion (in the next step only 
the naive algorithm). And a second version with only 3 steps of recursion. This 
will bound the memory requirements and give a speed up. This is a known 
heuristic (to stop the recursion early). But I don't know if it is better than 
the parameters for the algorithm found by the benchmark.

By the way: With "Winograd's method" I mean the one from Section 2.3 (page 10) 
from http://arxiv.org/abs/1106.1347 .
But please note that the survey article mentioned above is the first draft. It 
is not complete and the implementations are not optimized.

Best wishes, Ivo.

Am 18.07.2011 um 15:36 schrieb Simon King:

> Hi Ivo,
> 
> On 18 Jul., 13:32, hedtke <hed...@me.com> wrote:
>> With the in-memory variant I mean: "Boyer, Dumans, Pernet and Zhou: Memory 
>> efficient scheduling of Strassen-Winograd's matrix multiplication algorithm. 
>> International Symposium on Symbolic and Algebraic Computation 2009."
> 
> Of course, I can not speak for LinBox. But the stuff in
> sage.matrix.strassen could really be a bit more memory efficient: It
> uses more than 5 times the temporary memory that is needed even in the
> least memory efficient multiplication algorithm from the paper you
> cited.
> 
> So, I'm now trying to improve the performance of sage.matrix.strassen.
> 
> Cheers,
> Simon
> 
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