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From: Greg KH <greg@kroah.com>
To: "Irfan Ullah (울라 이르판)" <irfan@dke.khu.ac.kr>
Cc: kernelnewbies@kernelnewbies.org
Subject: Re: Software Prefetching using Machine learning
Date: Wed, 9 Oct 2019 09:44:27 +0200
Message-ID: <20191009074427.GB3842746@kroah.com> (raw)
In-Reply-To: <CA+mB8OyQesAb6e6QQ6HFcYkx1Jm7UCrxwnUxyzQ=myhQZD3fWg@mail.gmail.com>

On Wed, Oct 09, 2019 at 12:37:51PM +0900, Irfan Ullah (울라 이르판) wrote:
> Dear All,
> Thanks in advance. I am a PhD candidate, and currently I have started
> working on kernel development. My professor told me to implement this paper
> <https://arxiv.org/abs/1803.02329>. In this paper authors have used machine
> learning to predict the next missed addresses.They used instruction
> addresses (program counters PCs), and corresponding missed addresses as
> features to train the machine learning classifier.
> As  a kernel newbie, I don't know how to initiate the implementation. I am
> thinking to implement it in the following steps:
> 1- Saving instruction addresses (PCs), and corresponding missed addresses
> 2- Perform the machine learning
> 3-Do the prediction using machine learning classifier, and swap in/swap out
> the pages.

Are we going to get credit for doing your assignment?  :)

If this is for school, please work on this on your own.  And work with
your professor, perhaps this isn't even possible...

good luck!

greg k-h

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Thread overview: 12+ messages / expand[flat|nested]  mbox.gz  Atom feed  top
2019-10-09  3:37 Irfan Ullah (울라 이르판)
2019-10-09  7:44 ` Greg KH [this message]
2019-10-09 19:08 ` Valdis Klētnieks
2019-10-10  0:21   ` Ruben Safir
2019-10-10  0:24   ` Ruben Safir
2019-10-10  2:10     ` Irfan Ullah (울라 이르판)
2019-10-10  2:48       ` Irfan Ullah (울라 이르판)
2019-10-10  5:43         ` Valdis Klētnieks
2019-10-10  5:51         ` Kernel development tools (was Re: Software Prefetching using Machine learning) Valdis Klētnieks
2019-10-10  6:21           ` Irfan Ullah (울라 이르판)
2019-10-10  6:40             ` Greg KH
2019-10-10 13:22       ` Software Prefetching using Machine learning Rik van Riel

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