Radostin Stoyanov 3954ee09e5 contrib: Benchmark memory page compression ... Compression effectiveness depends on page contents and block size, while dump and restore costs can move independently of image size. The series needs a repeatable baseline that measures those trade-offs and rejects a fast result if restored memory is wrong. Add a root-only benchmark for zero, mixed, pseudorandom, text, and ELF-derived mappings. Compare uncompressed images with per-page LZ4 and a sweep of region sizes, rotate configuration order after a warmup, and report median storage, latency, and throughput from required CRIU statistics. Verify every restored mapping with SHA-256 and preserve artifacts when a trial fails. Bound workload startup and cleanup, handle termination signals, and make cache dropping an explicit, checked part of the methodology. Leave CRIU's compressed-page worker width unchanged unless requested, preserve an explicit automatic value of zero, and generate deterministic random input on Python versions before Random.randbytes(). Support JSON output for longer external runs. Assisted-by: Codex:GPT-5 Assisted-by: Claude:claude-fable-5 Signed-off-by: Radostin Stoyanov <rstoyanov@fedoraproject.org>		2026-07-14 10:17:01 +01:00
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main.py	contrib: Benchmark memory page compression	2026-07-14 10:17:01 +01:00
workload.py	contrib: Benchmark memory page compression	2026-07-14 10:17:01 +01:00