decimal_gda Performance

Measurement Boundary

just bench decimal-gda --target native runs the current Maremark suite in src/bench/decimal_gda and writes .tmp/bench/decimal-gda.jsonl plus its analysis file. The independent quick fixture can be run with python3 tools/run_gda_benchmark.py; it writes .tmp/bench/gda-quick-native.json and uses three native runs per cell. Neither artifact is a universal speed claim or a substitute for the conformance gate.

Workload

The Maremark suite measures add, subtract, multiply, divide, FMA, and parse at 1, 9, 18, 34, and 128 decimal digits. It compares the core GdaContext path with the full checked path and validates both against the core result before reporting layer overhead.

Reading Results

MAREMARK_JSONL is the raw event stream and MAREMARK_HOTSPOT reports paired core-versus-checked overhead. The quick fixture additionally records per- operation medians and dispersion. Interpret these measurements only for the recorded target, toolchain, fixture, and workload; they do not establish a cross-target threshold or a fixed latency bound.

Reproduction

just bench decimal-gda --target native
python3 tools/run_gda_benchmark.py
just bench all --target native

Use the same target and toolchain when comparing artifacts. Normal benchmark tests compile their plans but skip timing, so an explicit benchmark command is required for measurement.

Semantic Gate

The timing path is accepted only alongside the independent GDA state model and the pinned legal scalar corpus: 64,986/64,986 current rows and 16,124/16,124 legacy rows pass in the 0.7.1 audit. See Conformance, Design, and the 0.7.1 performance and semantic audit.