My lab had a GPU library for Random Forests on Images.

It was pretty fast but probably needs some updates:

https://github.com/deeplearningais/curfil


On 8/8/18 10:01 PM, Tommy Tracy wrote:
Dear Ta Hoang,

Accelerating decision tree ensembles (including Random Forest) is actually a current area of computer architecture research; in fact it is a principle component of my dissertation. Like Sebastian Raschka said, the GPU is not an ideal architecture for decision tree inference because at its core it is a pointer-chasing algorithm (low computation per memory access) that shows low memory locality. Scikit-Learn has done an excellent job with their von Neumann implementation utilizing things like predication and vectorization. If you're looking to go beyond what the CPU can give you, I would point you to FPGAs. If you're interested in discussing this further, let me know.

--
--
         Sincerely,
Tommy James Tracy II
     Ph.D Candidate
Computer Engineering
UniversityofVirginia


On Wed, Aug 8, 2018 at 8:50 PM, hoang trung Ta <tahoangtr...@gmail.com <mailto:tahoangtr...@gmail.com>> wrote:

    Dear all members,

    I am using Random forest for classification satellite images. I
    have a bunch of images, thus the processing is quite slow. I
    searched on the Internet and they said that GPU can accelerate the
    process.

    I have GPU NDVIA Geforce GTX 1080 Ti installed in the computer

    Do you know how to use GPU in Scikit learn, I mean the packages to
    use and sample code that used GPU in random forest classification?

    Thank you very much

-- *Ta Hoang Trung (Mr)*
    *
    *
    /Master student/
    Graduate School of Life and Environmental Sciences
    University of Tsukuba, Japan

    Mobile:  +81 70 3846 2993
    Email : ta.hoang-trung...@alumni.tsukuba.ac.jp
    <mailto:ta.hoang-trung...@alumni.tsukuba.ac.jp>
    tahoangtr...@gmail.com <mailto:tahoangtr...@gmail.com>
    s1626...@u.tsukuba.ac.jp <mailto:s1626...@u.tsukuba.ac.jp>
    *----
    *
    /Mapping Technician/
    Department of Surveying and Mapping Vietnam
    No 2, Dang Thuy Tram street, Hanoi, Viet Nam

    Mobile: +84 1255151344
    Email : tahoangtr...@gmail.com <mailto:tahoangtr...@gmail.com>

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