@@ -15,10 +15,11 @@ decompress and put the `raw_meshes` directory inside `testfiles`.
15151 . Download the dataset.
16162 . Build the binary with ` MANIFOLD_PAR ` and ` ASSIMP_ENABLE ` enabled. The
1717 binary should be inside ` build/extras ` (relative to the project root).
18- 3 . Run ` python do_ember_tests.py ` . This will take 10 minutes to an hour
19- depending on your machine. At the end, a ` benchmark.csv ` file will be
20- generated.
21- 4 . Run ` python analyze_ember_tests.py ` to analyze the result.
18+ 3 . Run the selected Ember benchmark cases through
19+ ` scripts/run_weekly_benchmarks.py ` , or run ` man_bench ` directly with the
20+ case arguments from ` testfiles/ember-benchmark-cases.json ` .
21+ 4 . Run ` python analyze_ember_tests.py ` to analyze the full ` benchmark.csv `
22+ result.
2223
2324## Files
2425
@@ -30,13 +31,8 @@ decompress and put the `raw_meshes` directory inside `testfiles`.
3031 file with the argument and timing information.
3132- ` testfiles/test_file/ember-benchmark-cases.json ` : JSON file describing each
3233 test case.
33- - ` do_ember_tests.py ` reads the description of the files and transforms
34- from the supplemental material of the Ember paper, and executes
35- man_bench on each pair. This creates a benchmark.csv file (remember
36- to remove that file again if you want a clean new run of data).
3734- ` analyze_ember_tests.py ` reads the benchmark.csv file and calculates
3835 statistics and does a plot.
3936- ` bug-case.json ` is a single test case that takes abnormally long.
4037- ` m3max_benchmarks.csv ` is the benchmarks file gotten by running on a
4138 Macbook Pro M3 Max (12 performance cores, 4 efficiency cores).
42-
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