Generate a CUDA kernel for fp16 square matrix multiply: C = A @ B, where A and B are both N x N fp16 matrices (row-major) and C is N x N fp16. Use a shared-memory TILED approach (e.g. 16x16 or 32x32 tiles): each block cooperatively loads tiles of A and B into shared memory, accumulates the partial products in fp32 for numerical stability, then writes the fp16 result. Two input tensors A and B, both N x N, fp16.
