int nnz!?!

[blgolden]

I know no one at EMP is reading this but...

Really!?! Number of non-zero values is passed as an int!?!

Can't we get that changed to an unsigned int?

Sure, no single GPU supports problems large enough to go beyond that count... yet. But what about when using the Host routines?

UPDATE: A quick note to anyone who might be reading this. After some extensive testing, I'm pretty sure this is a big problem with cula sparse. I have equations system that I can scale easily so I am able to make runs of varying NNZ easily. I also have written my own PCG solver. As I scale problems up I go from solutions that match my solver to geting "solver has broken down" and diverging solutions from cula sparse (both float and double versions) while my solver runs fine. Having an int data type makes no sense here. Even unsigned is not good for passing more then a few hundred million NNZ from host to GPU. E.g., cudamemcpy with sizeof(double)*large int will not return something sensible. I suspect something like hat is going on in the library?