Warp Execution and Divergence established the cost model: a warp pays for every path its 32 lanes collectively take, sequentially, so a branch only costs extra when lanes within the same warp disagree. This page is the applied counterpart — given that rule, what actually removes the cost in real kernels.
Warps and Warp Schedulers established that a warp scheduler issues one instruction to all 32 lanes of a warp at once. That raises an obvious question: what happens when those 32 threads disagree about which instruction to execute next, because a branch condition evaluated differently across lanes? The answer — the warp executes both outcomes and masks off the lanes that don't apply to each one — is the single most important cost model in CUDA kernel design, and getting it precise is the point of this page.