[mlpack] Fwd: mlpack:GSOC'17

[Yannis Mentekidis]

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 <abby37kapoor at gmail.com>
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 <ryan at ratml.org> 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
>> ryan at ratml.org | off his face this time."  - Lou
>>
>
>
>
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