I understand being frustrated; it's a natural consequence of being passionate about your own work, and anything that slows you down can feel like an obstacle.
Nevertheless I personally have a slightly different view: - Writing good documentation is not trivial, and for a sizable package can take days of effort. - It's wonderful that Dahua was willing to share code freely with others. Having a solid base to start with, especially from a developer as talented as Dahua, is a boon even when it takes some investment to use. His CUDA package has already been useful for several people. - I'm thrilled to hear about your contributions to the community, and I hope you keep them coming! But do keep in mind that few have given as much, in terms of code and documentation, as Dahua. Each package comes with its own maintenance burden, and at a certain point one reaches a limit. It would be great if other people can help share the load. One thing that would surely be a help would be to submit a pull request to CUDA.jl that provides the kind of information to others that you wish you had received yourself. Best, --Tim On Friday, April 18, 2014 01:39:44 PM Laszlo Hars wrote: > Jake: > > I also have volunteered some of my time to this community. E.g. I had to > adapt Gaston to Windows systems, and documented the effort. > > The description of a package listed in the Julia website ought to contain > notes that a package was only tested under a certain OS, and should not be > assumed to work elsewhere. I spent many hours with packages, which do not > tell this, and just don't work in my system. > > In the CUDA case: what is libcuda? Is it the CUDA runtime shared library? > What functions are expected and used from it? Adding these notes should not > take more than a few minutes of the author's time, but saves a lot of > frustration and time of a potential user. > > The lack of responses to my original question indicates that there are no > Windows users of CUDA, even though having a Windows CUDA package could have > been really useful: many of us have modern NVIDIA graphic cards, which > support CUDA, and speed up certain algorithms by orders of magnitude. Now I > may end up writing my own CUDA module, which is duplicating work.
