BTW did this include the changes I made in the trunk recently? I would also like to profile that code and see if we can squeeze out our Vectors and Matrices more. Could you point me to how I can run the 1M example.
Robin Robin Anil | Software Engineer | +1 312 869 2602 | Google Inc. On Thu, Apr 18, 2013 at 3:43 PM, Robin Anil <robin.a...@gmail.com> wrote: > I was just emailing something similar on Mahout(See my email). I saw the > TU Berlin name and I thought you would do something about it :) This is > excellent. One of the next gen work on Vectors is maybe investigating this. > > > Robin Anil | Software Engineer | +1 312 869 2602 | Google Inc. > > > On Thu, Apr 18, 2013 at 3:37 PM, Sebastian Schelter <s...@apache.org>wrote: > >> Hi there, >> >> with regard to Robin mentioning JBlas [1] recently when we talked about >> the performance of our vector operations, I ported the solving code for >> ALS to JBlas today and got some awesome results. >> >> For the movielens 1M dataset and a factorization of rank 100, the >> runtimes per iteration dropped from 50 seconds to less than 7 seconds. I >> will run some tests with the distributed version and larger datasets in >> the next days, but from what I've seen we should really take a closer >> look at JBlas, at least for operations on dense matrices. >> >> Best, >> Sebastian >> >> [1] http://mikiobraun.github.io/jblas/ >> > >
