First of all, are you using multiple contexts or a single one? If you only have one context, `Thread(pycuda.autoinit.context)` should be enough for Reikna (don't know about scikit-cuda, though).
Now if you have several contexts, things become more complicated. CUDA maintains a global context stack, if you want to use a specific context, you have to make sure it is on top of the stack (using corresponding PyCUDA functions). For Reikna, you must use a `Thread` object created for a specific context (or anything derived from it) only when that context is active. On Tue, Jul 31, 2018 at 5:07 PM, Rasmus Diederichsen < rasmusdiederich...@gmail.com> wrote: > I don't know cuda really and use the 3 libraries mentioned in the subject. > I time and again run into CUDA errors of the form "Invalid resource handle" > which appear in some cases, but not in others, i.e. the same function will > error or not depending on what ran before it, even if totally unrelated. I > gather from this that it has to do with state in CUDA, possibly mismanaging > contexts. But since it's hard to reproduce without all my code, I can't > open issues about this, so hopefully someone can just give me general > pointers. > > > - I am using the `pycuda.autoinit.context` for all the Reikna > `Thread`s. > - Neither reikna nor scikit-cuda seem to have functionality for > setting context globally or passing it to functions > - I have tried using my own context instead, but meet the same issues > > > What are the steps in general to ensure these issues don't come up? How > can I handle this when multiple files are in play? > > Cheers, > Rasmus > > _______________________________________________ > PyCUDA mailing list > PyCUDA@tiker.net > https://lists.tiker.net/listinfo/pycuda > >
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