What is occupancy and how can it be optimized?

Occupancy in the context of CUDA is the ratio of the number of active thread blocks (warps) on a GPU multiprocessor to the maximum possible number. High occupancy helps hide memory latencies and improve parallelism, leading to increased performance.

How to optimize occupancy:

• Reduce register usage per thread so that more threads can be scheduled simultaneously.
• Optimize shared memory usage to not limit the number of blocks.
• Choose the optimal block size (number of threads per block), usually a multiple of 32 (warp size).

However, high occupancy does not always guarantee better performance — it is important to balance resource usage and computational efficiency.