Explain GPU Register Spills and Their Performance Cost

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Quick Overview

Explain GPU register spills through live-variable pressure, compiler allocation, spill traffic, occupancy tradeoffs, and measured optimization choices.

Explain GPU Register Spills and Their Performance Cost

Company: AMD

Role: Software Engineer

Category: Software Engineering Fundamentals

Difficulty: medium

Interview Round: Onsite

What is a register spill in a GPU kernel, why does it happen, and how would you determine whether it is hurting performance? ### Constraints & Assumptions Discuss compiler-managed per-thread registers and the storage used when values cannot remain in registers. Do not confuse a spill with explicitly declared shared/local scratchpad memory; terminology differs across programming systems. ### Clarifying Questions What is the kernel's register usage and live-variable pressure? Is occupancy limited by registers? Does the compiler report spills? What memory traffic and stalls appear in profiling? ### What a Strong Answer Covers Live ranges, finite register allocation, spill loads/stores, occupancy tradeoffs, and changes justified by measurements. ### Follow-up Questions Can 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 allocation, spill traffic, occupancy tradeoffs, and measured optimization choices.

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Sep 14, 2026
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What is a register spill in a GPU kernel, why does it happen, and how would you determine whether it is hurting performance?

Constraints & Assumptions

Discuss compiler-managed per-thread registers and the storage used when values cannot remain in registers. Do not confuse a spill with explicitly declared shared/local scratchpad memory; terminology differs across programming systems.

Clarifying Questions Guidance

What is the kernel's register usage and live-variable pressure? Is occupancy limited by registers? Does the compiler report spills? What memory traffic and stalls appear in profiling?

What a Strong Answer Covers Guidance

Live ranges, finite register allocation, spill loads/stores, occupancy tradeoffs, and changes justified by measurements.

Follow-up Questions Guidance

Can 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?

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