Thanks I'll try this. :)
Best regards,
./francis
2011/8/4 Lev Givon <l...@columbia.edu>
> Received from Francis on Thu, Aug 04, 2011 at 08:58:33AM EDT:
> > Hi Lev,
> >
> > Basically I'm testing, part by part, my CUDA C code and porting my kernel
> > functions as PyCUDA source modules. The one I'm verifying right now is
> this
> > part:
> >
> > projection_module = """
> > __global__ void projection( char *List , int *l, int N, int L ) {
> >
> > int tid = blockIdx.x * 512 + threadIdx.x;
> > int idx1 = ceilf( tid / ( N - L + 1 ) );
> > int idx2 = tid % ( N - L + 1 );
> >
> > for ( int lcnt = 0; lcnt < L; lcnt++){
> > l[ (tid * L ) + lcnt ] = List[ (idx1 * N + idx2) + lcnt
> ];
> > }
> > }
> > """
> >
> > This works in CUDA C but surprisingly I get different values in PyCUDA.
> >
> > Best regards,
> >
> > ./francis
>
> What happens when you pass the -use_fast_math option to nvcc in
> PyCUDA? You can do this as follows:
>
> proj = SourceModule(projection_module,
> options=['-use_fast_math']).get_function('projection')
>
> L.G.
>
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