Hi,
How can I make a python type that corresponds to the device built-in
double2 both in that it has x,y fields _and_ aligned on 16 and not 8
bytes? I am passing it as an argument to the kernel that expects to
receive double2 instead it receives whatever is derived from
k = int(1)
l = int(2)
# how do I align the following
dbl2 = [('x','float64'), ('y','float64')]
a2 = np.array((-0.5,-0.5), dtype=dbl2)
...
kernel(k, l, a2, ...,arr.gpudata, block=(int(16),int(16),int(1)))
It either crashes or doesn't access properly arr.gpudata. I think what
happens is that a2 is not aligned when pushed into parameters stack as
expected by the kernel declaration in CUDA:
__global__ void kernel(int k, int l, double2 a2, ..., double2 *arr) {
if instead,
struct my_double2 {double x,y;};
__global__ void kernel(int k, int l, my_double2 a2, ..., double2 *arr) {
then it works.
What is the best way to pack arguments currently in PyCUDA?
Thanks
Igor
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