Hey all, Definitely agreed this would be nice! In our own work we've done element-wise addition, subtraction, and scalar multiplication of similarly partitioned matrices very efficiently with zipping. We've also done matrix-matrix multiplication with zipping, but that only works in certain circumstances, and it's otherwise very communication intensive (as Shivaram says). Another tricky thing with addition / subtraction is how to handle sparse vs. dense arrays.
Would be happy to contribute anything we did, but definitely first worth knowing what progress has been made from the AMPLab. -- Jeremy --------------------- jeremy freeman, phd neuroscientist @thefreemanlab On Sep 5, 2014, at 12:23 PM, Patrick Wendell <pwend...@gmail.com> wrote: > Hey There, > > I believe this is on the roadmap for the 1.2 next release. But > Xiangrui can comment on this. > > - Patrick > > On Fri, Sep 5, 2014 at 9:18 AM, Yu Ishikawa > <yuu.ishikawa+sp...@gmail.com> wrote: >> Hi Evan, >> >> That's sounds interesting. >> >> Here is the ticket which I created. >> https://issues.apache.org/jira/browse/SPARK-3416 >> >> thanks, >> >> >> >> -- >> View this message in context: >> http://apache-spark-developers-list.1001551.n3.nabble.com/mllib-Add-multiplying-large-scale-matrices-tp8291p8296.html >> Sent from the Apache Spark Developers List mailing list archive at >> Nabble.com. >> >> --------------------------------------------------------------------- >> To unsubscribe, e-mail: dev-unsubscr...@spark.apache.org >> For additional commands, e-mail: dev-h...@spark.apache.org >> > > --------------------------------------------------------------------- > To unsubscribe, e-mail: dev-unsubscr...@spark.apache.org > For additional commands, e-mail: dev-h...@spark.apache.org >
