1.1 KiB
1.1 KiB
gzip - evaluation
Artifacts saved in evaluation_artifacts
.
Performance
Using the command line
for i in $(seq 1 100); do
perf report 2>&1 >/dev/null | tail -n 1 \
| python ../hackbench/to_report_fmt.py \
| sed 's/^.* & .* & \([0-9]*\) & .*$/\1/g'
done
we save a sequence of 100 performance readings to some file.
Samples:
eh_elf
: 331134 unw/execvanilla
: 331144 unw/exec
Average time/unw:
eh_elf
: 83 nsvanilla
: 1304 ns
Standard deviation:
eh_elf
: 2 nsvanilla
: 24 ns
Average ratio: 15.7 Ratio uncertainty: 0.8
Distibution of unw_step
issues
eh_elf
case
- success: 331134 (99.9%)
- fallback to DWARF: 2 (0.0%)
- fallback to libunwind heuristics: 8 (0.0%)
- fail to unwind: 379 (0.1%)
- total: 331523
vanilla
case
- success: 331136 (99.9%)
- fallback to libunwind heuristics: 8 (0.0%)
- fail to unwind: 379 (0.1%)
- total: 331523