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] > <mailto:[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] > <mailto:[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] <mailto:[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] > <mailto:[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] > <mailto:[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] > <mailto:[email protected]> > https://mail.cct.lsu.edu/mailman/listinfo/hpx-users > <https://mail.cct.lsu.edu/mailman/listinfo/hpx-users> > >
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