Oh, I didn't know that. I should have given the link in this thread.
Regards, Aditya On Mon, Apr 3, 2017 at 8:30 PM, Patrick Diehl <[email protected]> wrote: > Sure you can do that, but you asked for feedback. > > . I hope you look at it and provide me with feedback if you have time so > that I can change it accordingly. > > But we can not look into your proposal until the deadline and thus can not > provide feedback. > > Best, > > Patrick > On 03/04/17 10:56 AM, Aditya wrote: > > Hi Patrick, > > Before the deadline, I think I can still modify the shared google doc and > reupload the pdf version of the update proposal. > Anyway, I have submitted the final pdf in the GSoC portal. > > Thanks, > Aditya > > > > > On Mon, Apr 3, 2017 at 4:59 PM, Patrick Diehl <[email protected]> > wrote: > >> Hi Aditya, >> >> first, we can only see the final submission after the deadline. Second, >> you can not change the final submission anymore. >> >> Best, >> >> Patrick >> >> Aditya <[email protected]> schrieb am Mo., 3. Apr. 2017, 04:30: >> >>> Hello Zahra and Kaiser, >>> >>> I have shared the final proposal with STE||AR Group through the GSoC >>> website. I hope you look at it and provide me with feedback if you have >>> time so that I can change it accordingly. >>> >>> Thanks a lot for the support. >>> >>> Regards, >>> Aditya >>> >>> >>> >>> >>> On Sun, Apr 2, 2017 at 8:12 PM, Zahra Khatami <[email protected]> >>> wrote: >>> >>> Hi Aditya, >>> >>> Thank you for your interest in the machine learning project. As Dr. >>> Kaiser explained, a compiler gathers static information for ML, then ML >>> will select the parameters, such as chunk sizes, for HPX's techniques, such >>> as loop. >>> We have worked on this project since a couple of months ago, and so far >>> we have got interesting results from our implementation. >>> Our focus in the Summer is to implement our technique on a distributed >>> applications. >>> So if you have a background in ML and distributed computing, it would be >>> enough to work on this topic. >>> I am pretty sure that this phase will result in a conference paper as >>> its new and super interesting ;) >>> So if you are interested in this project, go ahead and write your >>> proposal before its deadline. >>> >>> >>> >>> 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 Sun, Apr 2, 2017 at 7:04 AM, Hartmut Kaiser <[email protected] >>> > wrote: >>> >>> Hey Aditya, >>> >>> > It would be great if some of you could guide me through the project >>> > selection phase so that I can make my proposal as soon as possible and >>> get >>> > it reviewed too. >>> >>> The machine learning project aims at using ML techniques to select >>> runtime parameters based on information collected at compile time. For >>> instance in order to decide whether to parallelize a particular loop the >>> compiler looks at the loop body and extracts certain features, like the >>> number of operations or the number of conditionals etc. It conveys this >>> information to the runtime system through generated code. The runtime adds >>> a couple of dynamic parameters like number of requested iterations and >>> feeds this into a ML model to decide whether to run the loop in parallel or >>> not. We would like to support this with a way for the user to be able to >>> automatically train the ML model on his own code. >>> >>> I can't say anything about the Lustre backend, except that Lustre is a >>> high-performance file system which we would like to be able to directly >>> talk to from HPX. If you don't know what Lustre is this is not for you. >>> >>> All to All communications is a nice project, actually. In HPX we sorely >>> need to implement a set of global communication patterns like broadcast, >>> allgather, alltoall etc. All of this is well known (see MPI) except that we >>> would like to adapt those to the asynchronous nature of HPX. >>> >>> HTH >>> Regards Hartmut >>> --------------- >>> http://boost-spirit.com >>> http://stellar.cct.lsu.edu >>> >>> >>> > >>> > Regards, >>> > Aditya >>> > >>> > >>> > >>> > On Sun, Apr 2, 2017 at 5:21 AM, Aditya <[email protected]> >>> wrote: >>> > Hello again, >>> > >>> > It would be great if someone shed light on the below listed projects >>> too >>> > >>> > 1. Applying Machine Learning Techniques on HPX Parallel Algorithms >>> > 2. Adding Lustre backend to hpxio >>> > 3. All to All Communications >>> > >>> > I believe I will be suitable for projects 2 and 3 (above). As part of >>> my >>> > undergrad thesis (mentioned in the earlier email) I worked with Lustre >>> > briefly (we decided, lustre was an overkill for our scenario as we'd >>> have >>> > to re organize data among nodes even after the parallel read). I have >>> > worked with MPI on several projects (my thesis and projects in the >>> > parallel computing course) and have a basic understanding of all to all >>> > communications work. >>> > >>> > If someone could explain what would be involved in project 1, it'd be >>> > great. >>> > >>> > Also, please let me know what is expected of the student in projects 2 >>> and >>> > 3. >>> > >>> > Thanks again, >>> > Aditya >>> > >>> > >>> >>> >>> >>> >>> _______________________________________________ >>> hpx-users mailing list >>> [email protected] >>> https://mail.cct.lsu.edu/mailman/listinfo/hpx-users >>> >> > >
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