benchmarking

Test the vendor claim on your workload, including quality, latency, scaling and operating costs. A lower peak or lower price alone does not settle it.

Define what the timer includes, give both implementations the same conditions, and keep the sample distribution. A useful benchmark explains the workload and comparison well enough for someone else to reproduce them.

Separate compilation, module loading and execution before judging a faster kernel. Define the artifact and startup evidence needed to release a compiler upgrade.

Derive the ideal gain from filling a partial wave, then account for partial outputs, reduction order, workspace and the epilogue before selecting split-K.

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

Compute MFU from a declared global token count and time interval. Check the accounting before judging the percentage or choosing an optimization.

Define a reproducible workload and service contract, account for every offered request, and choose a measured operating region with evidence and margin.

A repeated-prompt test measures one reuse pattern. Production gains depend on token-weighted reuse, routing, residency, alignment and the prefill share of latency; a falling hit rate does not uniquely identify eviction.

Verify the throughput definition and service outcomes, compare resolved configurations and execution traces, then isolate supported changes. Quantify capacity replacement correctly and choose rollback from the full release risk.

Determine what the replacement count measures, compare equivalent device exposure and investigate differences by cohort, location, age, software and policy. Job-interruption statistics cannot supply a hardware replacement baseline.

Write and verify tiled NumPy matmul, derive its logical footprint and distinguish a cache model from the causes of measured runtime.

Connect a performance change to its measured mechanism. Compare fair baselines and calculate how a local speedup affects the whole workload.

Build a learning habit around questions, source evidence and practical tests. Explain a real example without claiming work you did not perform.