Hello folks - I'm a Perl+PDL developer and my questions are for the PyCUDA dev team (i.e. Andreas et al.).
I've managed to hack together some CUDA (runtime) bindings for Perl that I've been using for my numerical research for a few months. However, the interface is far from complete. It basically supports CUDA's malloc, memcpy, and a couple of other important functions necessary for handling errors. (Because I use the runtime, function compilation is handled with Inline::C, or by writing straight XS, in case you know what that means.) It does not support any device querying stuff and it does not allow for any memory allocations apart from those supported by cudaMalloc. While it is far from complete, it covers all my needs, and would be useful for somebody who has learned out of Kirk and Hwu, since they only use cudaMalloc. I am familiar with CUDA's runtime API. My bindings work for the runtime API and I had intended to continue down this path. However, you chose to wrap the driver API. I am curious what other sorts of design decisions you have made, and whether they have worked out well or not for your implementation. Also, I'm curious if all of your bindings were written by-hand or if you found a way to automatically process the header files to generate bindings. Thanks! David -- Sent via my carrier pigeon. _______________________________________________ PyCUDA mailing list PyCUDA@tiker.net http://lists.tiker.net/listinfo/pycuda
