[hpx-users] Deciding Benchmarks for HPXCL

[#SESHADRI MADHAVAN#]

Hi HPX Community,

As a part of my GSoC task, I am to implement Benchmarks for HPXCL. I have 
surveyed some benchmarks in 
https://madhavan001.github.io/Benchmarks-accelerator-devices/ . Some benchmarks 
do not have existing implementations of the problem in both OpenCL and CUDA, 
and hence native kernels will have to be written.

Please guide me on choosing the appropriate benchmark for HPXCL. Kindly also 
let me know if more information is required regarding any of them.

Best Regards,
Madhavan
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Re: [hpx-users] Applying machine learning techniques on HPX algorithms

[#SESHADRI MADHAVAN#]

Hi Zara,

I have already submitted a proposal for HPX (HPXCL), so I won’t be submitting 
for this one.

But I shall chip in contribution for this one as well as I find this to be an 
interesting area. My summer is currently free, so I shouldn’t have a problem in 
contributing to this in addition to HPXCL. I will begin by taking a look at the 
code base [1] and shall discuss further with you.

Best Regards,
Madhavan

[1] https://github.com/STEllAR-GROUP/hpxML

From: Zahra Khatami [mailto:z.khatam...@gmail.com]
Sent: Friday, March 31, 2017 12:25 AM
To: hpx-users@stellar.cct.lsu.edu; #SESHADRI MADHAVAN# 
<madhavan...@e.ntu.edu.sg>
Subject: Re: [hpx-users] Applying machine learning techniques on HPX algorithms

Hi Madhavan,

Thank you for your interest. I would be happy to work with you on this project.
This project is mainly about combining machine learning techniques, compiler 
optimizations and runtime methods, which is a new and super interesting idea 
for our group at least ;)
We have implemented a major part in connecting these three areas together. 
However, we have tested it on a single node, not on a distributed version.
As you have worked with Hadoop, so I believe that you have a good background in 
a distributed computing area.
For the next step of this project, focused on a Summer, we plan to implement 
our proposed techniques on a distributed applications. The first phase of this 
would be implementing distributed machine learning techniques, such NN or SVM.
Then we can analyze big data and design a learning model for our algorithms.

So please start writing your proposal, emphasize on extending ideas about 
implementing distributed machine learning techniques with HPX and targeting 
them for tying compiler and runtime techniques.
The proposal should be submitted before deadline (April 3rd). So I would 
suggest you to give me a first draft earlier, so we can work together for its 
final submission.


Best Regards,

Zahra Khatami | PhD Student
Center for Computation & Technology (CCT)
School of Electrical Engineering & Computer Science
Louisiana State University
2027 Digital Media Center (DMC)
Baton Rouge, LA 70803


On Thu, Mar 30, 2017 at 11:13 AM, #SESHADRI MADHAVAN# 
<madhavan...@e.ntu.edu.sg<mailto:madhavan...@e.ntu.edu.sg>> wrote:
Hi Zahra,

Sorry, for high jacking the previous email thread, changed the subject in this 
one.

I have proposed the idea for working on HPXCL with Patrick, hence I shall not 
be proposing this as my GSoC project, but I would love to jump into "Applying 
machine learning techniques on HPX algorithms". The project seems interesting 
and I have had some background implementing Machine Learning algorithms on 
Hadoop, predominantly in Java. But I have been through the process of designing 
and optimizing algorithms for execution in parallel which I believe will be 
useful for this. Let me know how I can get started.

Best Regards,
Madhavan

From: 
hpx-users-boun...@stellar.cct.lsu.edu<mailto:hpx-users-boun...@stellar.cct.lsu.edu>
 [mailto:hpx-users-boun...@stellar.cct.lsu.edu] On Behalf Of Zahra Khatami
Sent: Thursday, March 30, 2017 11:56 PM
To: denis.bl...@outlook.com<mailto:denis.bl...@outlook.com>
Cc: hpx-users@stellar.cct.lsu.edu<mailto:hpx-users@stellar.cct.lsu.edu>
Subject: Re: [hpx-users] [GSoC 2017] Proposal for re-implementing 
hpx::util::unwrapped

Hi Denis,

I am so glad that you are interested in HPX GSOC.
I have looked at your github and your projects seems so interesting for me. 
Feel free to write your proposal and submit it before April 3rd. I would be 
happy to be your mentor, as I have found your background match with my current 
projects as well. If you go through

https://github.com/STEllAR-GROUP/hpx/wiki/GSoC-2017-Project-Ideas#re-implement-hpxutilunwrapped

You will find a project "Applying machine learning techniques on HPX 
algorithms", which I think it could be a good fit for you too. Our team has 
been working on it since 2-3 months ago and so far we have got interesting 
results, which are going to be prepared for a conference paper. In this project 
we are using LLVM and Clang LibTooling to implement a machine learning 
techniques on an HPX parallel algorithm, and we have applied and tested them on 
an hpx loop.
So as another option, you could look at this GSOC project idea and write a 
brief proposal about how you can implement it.

Best Regards,

Zahra Khatami | PhD Student
Center for Computation & Technology (CCT)
School of Electrical Engineering & Computer Science
Louisiana State University
2027 Digital Media Center (DMC)
Baton Rouge, LA 70803


On Thu, Mar 30, 2017 at 10:55 AM, Patrick Diehl 
<patrickdie...@gmail.com<mailto:patrickdie...@gmail.com>> wrote:
Hi Denis,

the ides sounds good, for GSoC, you should submit your proposal at their
official website. You can use this template [0] and our guidelines [1]
to prepare your proposal.  The deadline for

Re: [hpx-users] [GSoC 2017] Proposal for re-implementing hpx::util::unwrapped

[#SESHADRI MADHAVAN#]

Hi Zahra,

I have proposed the idea for working on HPXCL with Patrick, hence I shall not 
be proposing this as my GSoC project, but I would love to jump into "Applying 
machine learning techniques on HPX algorithms". The project seems interesting 
and I have had some background implementing Machine Learning algorithms on 
Hadoop, predominantly in Java. But I have been through the process of designing 
and optimizing algorithms for execution in parallel which I believe will be 
useful for this. Let me know how I can get started.

Best Regards,
Madhavan

From: hpx-users-boun...@stellar.cct.lsu.edu 
[mailto:hpx-users-boun...@stellar.cct.lsu.edu] On Behalf Of Zahra Khatami
Sent: Thursday, March 30, 2017 11:56 PM
To: denis.bl...@outlook.com
Cc: hpx-users@stellar.cct.lsu.edu
Subject: Re: [hpx-users] [GSoC 2017] Proposal for re-implementing 
hpx::util::unwrapped

Hi Denis,

I am so glad that you are interested in HPX GSOC.
I have looked at your github and your projects seems so interesting for me. 
Feel free to write your proposal and submit it before April 3rd. I would be 
happy to be your mentor, as I have found your background match with my current 
projects as well. If you go through

https://github.com/STEllAR-GROUP/hpx/wiki/GSoC-2017-Project-Ideas#re-implement-hpxutilunwrapped

You will find a project "Applying machine learning techniques on HPX 
algorithms", which I think it could be a good fit for you too. Our team has 
been working on it since 2-3 months ago and so far we have got interesting 
results, which are going to be prepared for a conference paper. In this project 
we are using LLVM and Clang LibTooling to implement a machine learning 
techniques on an HPX parallel algorithm, and we have applied and tested them on 
an hpx loop.
So as another option, you could look at this GSOC project idea and write a 
brief proposal about how you can implement it.

Best Regards,

Zahra Khatami | PhD Student
Center for Computation & Technology (CCT)
School of Electrical Engineering & Computer Science
Louisiana State University
2027 Digital Media Center (DMC)
Baton Rouge, LA 70803


On Thu, Mar 30, 2017 at 10:55 AM, Patrick Diehl 
> wrote:
Hi Denis,

the ides sounds good, for GSoC, you should submit your proposal at their
official website. You can use this template [0] and our guidelines [1]
to prepare your proposal.  The deadline for the submission is

> April 3 16:00 UTC Student application deadline

We are looking forward to review your proposal.

Best,

Patrick

[0] https://github.com/STEllAR-GROUP/hpx/wiki/GSoC-Submission-Template

[1] https://github.com/STEllAR-GROUP/hpx/wiki/Hints-for-Successful-Proposals

On 30/03/17 11:29 AM, Denis Blank wrote:
> Hello HPX Developers,
>
> I'm Denis, an Informatics Student at the Technical University of Munich, 
> Germany.
>
> In the summer semester, I'm transitioning to my master's program and
> thus I will finally have enough time to have a chance on participating at 
> GSoC.
>
> I'm very keen on Open-Source because you always learn something new about 
> various topics
> not covered in studies, and you get connected to other developers around the 
> world.
>
> Thus I'm highly active on GitHub (https://github.com/Naios), also, I recently 
> started
> to attend various conferences such as the MeetingC++ or EuroLLVM.
>
> In my spare time, I'm working on side projects very related to the field HPX 
> is covering,
> like a library for compile-time known continuation chaining - continuable [0].
>
> I'm also a member of the TrinityCore [1] Open-Source project where I'm 
> contributing
> for 6 years now (beside of other projects like fmtlib or ANTLR).
>
> HPX is very attractive for me as a potential GSoC project,
> because of its high-quality codebase as well as its impact on
> the today's important infrastructure for parallel computing.
>
> During my work on previous side projects and contributions, I gathered
> significant knowledge in C++ template meta-programming as well as designing 
> good API's.
> My bachelor's thesis was also about improving meta-programming in static 
> languages.
>
> Thus I want to work on improving the API of HPX especially the 
> `hpx::util::unwrapped` function.
> While browsing the issue tracker I spotted other related issues,
> not mentioned in the existing proposal, such as the requirement
> of a unified waiter API for arbitrary objects (#1132 [2]).
>
> My plans for a potential GSoC stipend embrace a complete rewrite of the
> `hpx::util::unwrapped` function, in order to use a new designed waiter
> and unwrapping internal API which picks up the ideas mentioned in #1132,
> to fully support the requirements of issue #1404, #1400 and #1126.
> The API should also replace the existing internal solutions of:
>
>   - `dataflow`
>   - `wait_all`
>   - `when_all`
>
> in order to remove a lot of duplicated code (`when_all_frame` and 
> `wait_all_frame`),
> as well as to make the API consistent across