This is not specific to pycuda, but to cuda itself. It is a new feature (~unified addresse space) that they have that request this. I don't know how to disable this feature as I don't use it.
Fred On Wed, May 23, 2012 at 10:35 AM, <w...@synchroverge.com> wrote: > Hi everyone, > > I'm working on a reasonably large piece of Python software which uses PyCUDA > for the performance-critical section of the code. I've been experiencing a > memory leak, and while trying to track it down I've noticed that PyCUDA has > a large virtual memory footprint -- somewhere in the ballpark of 36GB even > when no arrays have yet been allocated. Is this typical for PyCUDA, or is > there perhaps something wrong with my setup? > > Thanks, > ' > Brendan Wood > > _______________________________________________ > PyCUDA mailing list > PyCUDA@tiker.net > http://lists.tiker.net/listinfo/pycuda _______________________________________________ PyCUDA mailing list PyCUDA@tiker.net http://lists.tiker.net/listinfo/pycuda
