Was Auslastung wirklich bedeutet

Each GPU core, called an SM, can keep many warps resident at once. Occupancy measures how full that capacity really is. 🎯

Occupancy is the ratio of active warps on an SM to the maximum warps that SM can hold. More resident warps means a fuller machine.

When one warp stalls on a slow memory read, the SM instantly runs another ready warp. That swap is how the GPU hides latency.

Every architecture sets a ceiling, often 64 warps per SM. Occupancy compares your kernel against that hardware limit.

Theoretical occupancy is what your launch config allows on paper. Achieved occupancy is what actually ran, measured by a profiler.

If an SM holds 64 warps but your kernel keeps only 32 resident, your occupancy is 50%. Half the latency-hiding power sits idle.

Occupancy is always counted in warps, never single threads. A warp is 32 threads, so a 256-thread block is exactly 8 warps.

The scheduler splits each resident block into warps. So blocks per SM times warps per block gives the active warp count.

Three resources cap occupancy: registers per thread, shared memory per block, and the SM warp limit. The tightest one wins.

More occupancy usually hides latency better, but past a point it brings no extra gain. It is a tool, not the final goal.

Profilers like Nsight Compute report achieved occupancy right next to your kernel. That number is your tuning starting point.

Think about what occupancy actually measures.

You learned that occupancy is active warps over the SM maximum, counted in warps, and it powers latency hiding. 🚀