Performance and resource management

1. Measure before optimizing

Do not publish performance claims from intuition. A useful benchmark identifies the input dimensions, format, operation, runtime, hardware, warm-up, number of iterations, and the statistic reported, such as median and tail latency.

2. What to measure

Depending on the actual implementation, measure input decode duration; processing duration by stage; output encode duration; total wall-clock duration; peak memory or a defensible proxy; output file size; cancellation latency; and behavior under repeated and concurrent operations.

Do not add unsupported metrics merely because they look impressive on a dashboard.

3. Image memory estimates

An uncompressed RGBA buffer uses approximately four bytes per pixel before accounting for extra copies, masks, model memory, decoder overhead or intermediate buffers. For example, a 4000 × 3000 RGBA image requires about 48,000,000 bytes (roughly 45.8 MiB) for one buffer alone. Multiple full-size copies can multiply that cost.

Use this estimate to motivate input limits and ownership discipline, not as a claim about Kraul's measured memory consumption.

4. User experience

Long operations should not block the interface unnecessarily. If the implementation supports workers or asynchronous processing, document where work runs and how progress/cancellation are communicated. Do not claim progress reporting if only start/end events exist.

5. Optimization order

1. Reproduce the slow case.
2. Profile stages independently.
3. Reduce unnecessary decode/encode cycles and copies.
4. Bound concurrency and intermediate storage.
5. Consider workers, streaming or tiled processing only if the runtime and algorithm support them.
6. Re-run correctness and visual regression tests after every optimization.

6. Benchmark reporting template

For each result record the commit/version; environment and runtime; source dimensions and format; operation and options; number of repetitions; median and p95 if sample size is sufficient; memory measurement method; and known caveats.

7. Current status

No Kraul runtime source or benchmark suite is present in the current repository tree. No speed, latency, memory or throughput claims should be published until measurements are made.