Hi, > During the last couples of days, I've explored a bit how Machine > Learning could help predictive autotuning, it seems that some techniques > have led to pretty good results in autotuning image processing kernels > for GPUs. > Of course, it is out of question to rewrite complicated C++ Machine > Learning algorithm when some already exist in the public domain. Anyway, > I think that building a nice autotuning environment will introduce a lot > of new dependencies (Qt, some ML packages, etc...), and will result in a > binary rather than a library. It seems to me that it would require a > different build system, optional since we can ship reasonable > precompiled kernels. What do you think about having the autotuner as a > separate repository or a submodule?
Since the 'main' ViennaCL library is supposed to be fairly decoupled from an autotuning environment sitting on top, I think the best path to go is to have a separate repository underneath github.com/viennacl/ If, on the other hand, this is supposed to be a research project involving lots of experimentation rather than a true 'application', you may also just use your own repository on Github. An integration at some later stage is, or course, no problem :-) Best regards, Karli ------------------------------------------------------------------------------ October Webinars: Code for Performance Free Intel webinars can help you accelerate application performance. Explore tips for MPI, OpenMP, advanced profiling, and more. Get the most from the latest Intel processors and coprocessors. See abstracts and register > http://pubads.g.doubleclick.net/gampad/clk?id=60134071&iu=/4140/ostg.clktrk _______________________________________________ ViennaCL-devel mailing list ViennaCL-devel@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/viennacl-devel
