Hello Abhinav, As far as I am aware, the only parallel algorithms in mlpack currently are LSH and DET (methods/det/ directory, files dtree_impl.hpp and dt_utils_impl.hpp)
If you're not comfortable with OpenMP, I would suggest the LLNL tutorial found here: https://computing.llnl.gov/tutorials/openMP/ I am afraid I am not the best person to answer about issue #401, sorry about that :( I saw Ryan opened a few enhancement issues earlier today, specifically the 5 newest ones on the issues page. Take a look at them as well, maybe you'll find something there that you like! On Wed, Feb 22, 2017 at 5:03 PM, abhinav kumar <[email protected]> wrote: > Hey, > Thank you for reply. > I was going through the mlpack source code and found SGD is already > implemented. So I have to write the implementation of SCD and its code > should be written with OpenMP along with code of SGD ? I have seen there is > OpenMP implementation of LSH search and this ticket number (#179) > <http://www.mlpack.org/trac/ticket/179> is about parallelism of mlpack. > Can you point me to other OpenMP implementation in mlpack so that I can > study them. > > I was looking at the Issue 401 > <https://github.com/mlpack/mlpack/issues/401> on github and I thought it > is a good starter for me to work on. It will help me to learn convex > optimization and make a contribution to mlpack. I have some doubt ( or less > knowledge ) regarding that how constraints to be written for that. It would > be great if you can point me some resource regarding that. > > Another thing is there any other issue or work I should look for this > project ? > > Thanks, > > Abhinav Kumar > NIT Srinagar > > > On Fri, Feb 10, 2017 at 8:41 PM, Ryan Curtin <[email protected]> wrote: > >> On Fri, Feb 10, 2017 at 12:16:02AM +0530, abhinav kumar wrote: >> > Hello everyone, >> > Myself Abhinav Kumar, 4th year computer science student from NIT >> Srinagar, >> > India. I am a machine learning and parallel computing enthusiast and >> worked >> > on unsupervised learning during my previous internship. I was learning >> > about ml programing then I came through mlpack. Its a nice and promising >> > software. >> > I have experience of using armadillo,cmake and lapack for my ml and c++ >> > programs. I have made contribution to gnome software. >> > I like to contribute to mlpack and be part of GSOC'17 through mlpack >> > organisation. I have compiled mlpack from source on my computer and used >> > some of its algorithm. I am also familiar with git system and have a >> good >> > experience with c++. I have read about template SFINAE and reading about >> > policy based design (as provided in mlpack documentation). >> > >> > I was going through mlpack GSOC list 2017 and I like to work on - >> > * Parallel stochastic optimization methods * >> > I am very much interested to work on this project.I have found these >> paper >> > related to this project - >> > for SCD (https://arxiv.org/pdf/1311.1873.pdf) >> > for SGD (http://martin.zinkevich.org/publications/nips2010.pdf) >> > I have also found that this project was listed in GSOC 2015 and archive >> > related to this is - Archive March 2015 >> > <http://knife.lugatgt.org/pipermail/mlpack/2015-March/001658.html> >> > For Martin Zinkevich paper, it was commented as >> > " I think it makes more sense in a distributed setting (where >> communication >> > is much more expensive than in a shared memory >> > setting). " So, I have to look for other paper on it. >> > For this project , I need to learn convex optimization and this course >> by >> > Stanford University >> > <http://online.stanford.edu/course/convex-optimization-winter-2014> >> can be >> > really helpful. If there is any other resources to look for please >> direct >> > me to that. >> > I have some experience of creating multi-thread program on c# and i >> think >> > by using that knowledge and studying tutorials based on c++ threads I >> can >> > do a great work on this project. >> > >> > It would be a great opportunity to be part of this organisation and >> > contribute to mlpack. >> >> Hi Abhinav, >> >> There are several other mailing list threads, but since you have already >> searched the archive, you have probably found them. An implementation >> should be written with OpenMP to match the rest of the parallel code in >> mlpack, so keep that in mind while you are preparing your plans. >> >> Let me know if there is anything else I can clarify. >> >> Thanks, >> >> Ryan >> >> -- >> Ryan Curtin | "And tell the engineers to wipe that stupid smile >> [email protected] | off his face this time." - Lou >> > > > > _______________________________________________ > mlpack mailing list > [email protected] > http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack >
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