I am looking at some CUDA Support Vector Machine implementation but I did not find anything interesting; there is cuSVM http://patternsonascreen.net/cuSVM.html (but it is only for MATLAB, I need something that can run without MATLAB), CUDA implementation of libsvm http://mklab.iti.gr/project/GPU-LIBSVM (but this CUDA implementation uses only RBF kernel!! I need a POLYNOMIAL KERNEL!!).
Thx for replying ;-)… it is not so simple to me to implement efficient support vector machine from scratch or from LIBSVM (there are many stuffs that I do not understand from source…), but I am figuring out how to use cuSVM poly kernel in my project. In the last days I have found another svm CUDA implementation gpusvm: http://www.cs.berkeley.edu/~catanzar/GPUSVM/… it is seem suit for my purpose.
In the last days I have found gpusvm project: http://www.cs.berkeley.edu/~catanzar/GPUSVM/ there are some bugs that I should fix quickly (leakage and random crash) but seem works well in data set classification (when it does not crash…)
did you find a solution ? I’ve also looked at cusvm, multisvm and gpu-libsvm. there’s also an interesting publication of linear cuda svm in http://www.springerlink.com/content/u803484488376376/ but source not published and author not responding. I tried getting cusvm to work on linux but not with much successs.
Lol then you have adapted SVMlight http://svmlight.joachims.org/ from CPU to GPU…can you share your source with CUDA community (for above people… at the moment I am using only libsvm GPU for CUDA, but I am curious about your implementation and benchmark comparison SVMlight GPU vs SVMlight CPU vs libsvm GPU)??
I’ll be mostly glad to do that. Nevertheless, I canâ€™t do it right now because Iâ€™m using that in my MSc thesis. Once itâ€™s published, defended and accepted, I swear that itâ€™ll be posted =) (Which may happen in a couple of months at most).
Are there any updates on this thread? I am looking for a good GPU accelerated SVM. Most have parallelized just the kernel, I can find only one that has parallelized both the kernel and the solver function (KMLib @ https://github.com/ksirg/KMLib).
Unfortunately, I can not get KMLib to compile, plus it is based on Cudafy and an old version of CUDA. I love the .NET wrapper too! If only it would work for me…
I am keen to here if anyone has come across a CUDA5.5 or, even better, CUDA6.0RC based solution. I am also happy to consider OpenCL or other GPU languages compatible with the TITAN card also.
Language of choice is C++ or C#. Environment is VS 2012 or 2013.
that implementation operates on dense floating point data. It can run for up to 32 lambdas in parallel, and return the respective u and z vectors (for each lambda), as well as an integer vector with the number of iterations it took for convergence for its respective lambda.
With sufficient incentive I could write the SVM in CUDA in a couple days, re-using parts of the code. While that version is meant to be called from MATLAB, it would be no problem to write an executable, but C++ only , as C# is slow.