Explain GPU Register Spills and Their Performance Cost

Define a GPU kernel register spill, explain why it occurs, and describe how you would check whether it is hurting performance.

Constraints & Assumptions

Consider compiler-controlled per-thread registers and the backing storage when values can no longer stay in registers. Avoid mixing up a spill with programmer-declared shared or local scratchpad; terminology differs across programming environments.

Clarifying Questions

What is the kernel’s register usage and live-variable pressure? Are registers the occupancy bottleneck? Does the compiler emit spill diagnostics? What memory traffic and stalls show up in profiling?

What a Strong Answer Covers

Live intervals, limited register budget, spill load/store operations, occupancy tradeoffs, and changes supported by measured data.

Follow-up Questions

Could forcing a lower register limit make a kernel slower? How can unrolling or large local arrays affect pressure? When might recomputation be cheaper than preserving a value?

Overview: Explain GPU register spills through live-variable pressure, compiler register allocation, spill memory traffic, occupancy tradeoffs, and optimization choices backed by measurement.