Hi Qifan, thanks for your feedback. You're right, the builtin functions cholesky, inverse, eigen, solve, svd, qr, and lu are currently only supported as single-node operations because they're still implemented via Apache commons.math.
However, there is an experimental script for distributed cholesky [1] which uses a recursive approach (with operations that allow for automatic distributed computation) for matrices larger than a user-defined block size. Once blocks become small enough, we use again the builtin cholesky. Graduating this script would require a broader set of experiments (and potential improvements) but it simply did not have the highest priority so far. You might want to give it a try though. Thanks again for your feedback - we'll consider a higher priority for these distributed operations when discussing the roadmap for the next releases. [1] https://github.com/apache/systemml/blob/master/scripts/staging/scalable_linalg/cholesky.dml Regards, Matthias On Sat, Apr 21, 2018 at 2:15 PM, Qifan Pu <qifan...@gmail.com> wrote: > Hi, > > I would love to do distributed cholesky on large matrix with SystemML. I > found two related jiras (SYSTEMML-1213, SYSTEMML-1163), but AFAIK, this is > currently not implemented? I just wanted to check. > > Best, > Qifan
