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An AI-generated kernel passes random tests and claims a 3x speedup. What would you verify?

Review the input contract, adversarial cases, evaluator independence and compiled baseline before trusting a generated GPU kernel or its reported speedup.

Updated Oct 2026 · Learn how AI infrastructure works through explanations, worked examples and diagrams, then practise applying it to interview questions.

Review the input contract, adversarial cases, evaluator independence and compiled baseline before trusting a generated GPU kernel or its reported speedup.

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Work through the numbers

Change the assumptions in a free calculator, then explain what the result establishes and what still needs measurement.

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The concepts behind this question

Use these concept explanations to review the ideas behind this question.

⚡ Kernels & Compilers🔒 Premium

Kernel Correctness ContractsA fast GPU kernel is useful only for inputs it handles correctly. Define shapes, strides, dtypes, numerical tolerance, storage ownership and synchronization before timing a replacement.

🚀 Inference & Serving🔒 Premium

Structured Outputs and Constrained DecodingConstrained decoding rules out tokens that break a grammar. Follow a two-choice example through masking, completion and rollback, then separate valid structure from correct, authorized tool arguments.

⚡ Kernels & Compilers

Kernel FusionKernel fusion combines operations so intermediate results can stay on-chip. It can reduce memory traffic and launch overhead, but may increase resource pressure.

⚡ Kernels & CompilersSign in

Triton Programming ModelTriton expresses GPU work as operations on blocks of values. You choose shapes, addresses and masks while the compiler maps the work onto hardware.

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