Add booster strong scaling configs
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@ -4,6 +4,9 @@ generate-batch-strong-cpu:
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generate-batch-strong-gpu:
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python scripts/substitute.py strong-batch.j2 < strong-gpu.json
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generate-batch-strong-booster:
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python scripts/substitute.py strong-batch.j2 < strong-booster.json
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clean-logs:
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rm logs/*
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1
experiments/eval/data/strong-booster-timings.json
Normal file
1
experiments/eval/data/strong-booster-timings.json
Normal file
File diff suppressed because one or more lines are too long
9
experiments/eval/data/strong-booster.tsv
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9
experiments/eval/data/strong-booster.tsv
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@ -0,0 +1,9 @@
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label nodes tasks mean_time std_time speedup speedup_std speedup_error
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1 1 1 161.08257980000002 1.0725827874500897 1.0 0.0066585895804611986 0.004614167168572558
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1 1 2 109.2771463 1.3498701967829918 1.474073813730255 0.018208823861030076 0.012618071172974463
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1 1 4 94.5763083 2.921107861707173 1.7032022363258181 0.052605536545441436 0.03645377698685362
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2 2 8 75.06436665 5.345617315509918 2.145926049720424 0.15281950626022228 0.10589851499069955
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4 4 16 42.842002025 1.5314070839490197 3.759921856733072 0.13440013758310768 0.09313454370387199
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8 8 32 16.40522446875 4.395440141154071 9.818980539208297 2.6307924825691393 1.823046180232846
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16 16 64 9.361684956249999 5.010216046116417 17.206579857449583 9.208671612370724 6.381283859970849
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32 32 128 5.214438346875 0.113661681579046 30.891645290338204 0.6733604113945479 0.4666149588180552
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@ -1,10 +1,10 @@
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label nodes tasks mean_time std_time speedup speedup_std
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1 1 48 1953.3832839708334 14.087268287606769 1.0 0.007211727674340593
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2 2 96 1046.3540047312501 6.0880471399828595 1.866847429396085 0.013463195270347342
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4 4 192 566.0709002166666 5.005298021298787 3.4507749527897755 0.024886049224955378
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8 8 384 318.1225953708333 9.706195475255436 6.1403475024896865 0.04428251401377301
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16 16 768 178.56471887994792 9.393026972005948 10.939357428631386 0.07889166670756431
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32 32 1536 99.82801128216144 1.4413062581268035 19.56748670921274 0.14111538541812124
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64 64 3072 55.75610567220052 1.0303316198245824 35.034428255357376 0.25265875580386077
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128 128 6144 31.589132888118492 0.32226687791817415 61.83719226764697 0.4459529907801098
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256 256 12288 19.11704500200738 0.18528928846832715 102.18018965617955 0.7368957015128405
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label nodes tasks mean_time std_time speedup speedup_std speedup_error
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1 1 48 1953.3832839708334 14.087268287606769 1.0 0.007211727674340593 0.004711662080569187
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2 2 96 1046.3540047312501 6.0880471399828595 1.866847429396085 0.010861959816590314 0.007096480413505672
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4 4 192 566.0709002166666 5.005298021298787 3.4507749527897755 0.030512356378918384 0.019934739500893344
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8 8 384 318.1225953708333 9.706195475255436 6.1403475024896865 0.18734731205020752 0.12240024387280224
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16 16 768 178.56471887994792 9.393026972005948 10.939357428631386 0.5754422263707719 0.375955587895571
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32 32 1536 99.82801128216144 1.4413062581268035 19.56748670921274 0.28251330150299214 0.18457535698195485
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64 64 3072 55.75610567220052 1.0303316198245824 35.034428255357376 0.6474103379133267 0.42297475410337343
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128 128 6144 31.589132888118492 0.32226687791817415 61.83719226764697 0.6308523555205254 0.41215687227340997
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256 256 12288 19.11704500200738 0.18528928846832715 102.18018965617955 0.9903672160087601 0.6470399144590566
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@ -1,9 +1,9 @@
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label nodes tasks mean_time std_time speedup speedup_std
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1 1 1 316.56674059999995 1.3298279828832311 1.0 0.004200782370133899
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1 1 2 239.7297573 1.3705192585818793 1.3205150005797797 0.005547196133932895
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1 1 4 150.86725470000002 1.463195211854327 2.098313124537819 0.008814556780579045
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2 2 8 103.758313 1.3959932139830615 3.051001230137579 0.012816592178818781
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4 4 16 56.423368849999996 0.8293394846143929 5.610560784514376 0.02356874483015261
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8 8 32 24.168551143749998 0.5503559531334744 13.09829202078025 0.055023074199759194
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16 16 64 15.05716248125 0.04648043269670786 21.024329185144023 0.08831863138484462
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32 32 128 9.9111531140625 0.08848604506395903 31.940455056721632 0.1341749004963304
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label nodes tasks mean_time std_time speedup speedup_std speedup_error
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1 1 1 316.56674059999995 1.3298279828832311 1.0 0.004200782370133899 0.002910993666206366
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1 1 2 239.7297573 1.3705192585818793 1.3205150005797797 0.007549297425250635 0.00523139621453709
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1 1 4 150.86725470000002 1.463195211854327 2.098313124537819 0.020350616990413285 0.014102258089746373
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2 2 8 103.758313 1.3959932139830615 3.051001230137579 0.041049019495199714 0.028445519245192213
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4 4 16 56.423368849999996 0.8293394846143929 5.610560784514376 0.08246688711191473 0.057146637198176795
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8 8 32 24.168551143749998 0.5503559531334744 13.09829202078025 0.29826872726631265 0.20668968287257275
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16 16 64 15.05716248125 0.04648043269670786 21.024329185144023 0.06490066896072916 0.044973869063161365
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32 32 128 9.9111531140625 0.08848604506395903 31.940455056721632 0.28516203039001964 0.19760720531719309
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@ -3,6 +3,7 @@
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import argparse
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import json
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import math
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def print_table(data, spec):
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@ -31,6 +32,9 @@ if __name__ == "__main__":
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"mean_time": lambda job: job["means"]["TimeStep"],
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"std_time": lambda job: job["stds"]["TimeStep"],
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"speedup": lambda job: jobs[0]["means"]["TimeStep"] / job["means"]["TimeStep"],
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"speedup_std": lambda job: jobs[0]["stds"]["TimeStep"] / job["means"]["TimeStep"],
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# Standard deviation scaled to speedup
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"speedup_std": lambda job: (jobs[0]["means"]["TimeStep"] / job["means"]["TimeStep"]) * (job["stds"]["TimeStep"] / job["means"]["TimeStep"]),
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# 95% confidence interval
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"speedup_error": lambda job: (jobs[0]["means"]["TimeStep"] / job["means"]["TimeStep"]) * (job["stds"]["TimeStep"] / job["means"]["TimeStep"]) / math.sqrt(len(jobs)) * 1.96,
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}
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print_table(jobs, scaling_spec)
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34
experiments/eval/scripts/generate-strong-booster-configs.py
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34
experiments/eval/scripts/generate-strong-booster-configs.py
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@ -0,0 +1,34 @@
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#!/usr/bin/env python
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import copy
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import json
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from pathlib import Path
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SIZE = [384, 384, 384]
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with (Path(__file__).parent.parent / "templates" / "strong-booster.json").open(encoding="utf8") as f:
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template = json.load(f)
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configs = [
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[ 1, 1, 1],
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[ 1, 1, 2],
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[ 1, 2, 2],
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[ 2, 2, 2],
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[ 2, 2, 4],
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[ 2, 4, 4],
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[ 4, 4, 4],
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[ 4, 4, 8],
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]
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out_path = Path(__file__).parent.parent / "generated" / "config"
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for c in configs:
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nc = copy.deepcopy(template)
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nc["Geometry"]["blockcount"] = c
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nc["Geometry"]["blocksize"] = [bs // bc for bc, bs in zip(c, SIZE)]
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nc_out_path = out_path / f"strong-booster-{c[0]:02}-{c[1]:02}-{c[2]:02}.json"
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print(f"Dumping {(c[0] * c[1] * c[2])} to {nc_out_path}")
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with nc_out_path.open("w", encoding="utf8") as f:
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json.dump(nc, f)
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@ -76,6 +76,7 @@ if __name__ == "__main__":
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p = argparse.ArgumentParser(description="Load and analzye data from nastja timing files")
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p.add_argument("jobid", nargs="+")
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p.add_argument("--prettify", action="store_true")
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p.add_argument("--dump-timings", action="store_true")
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args = p.parse_args()
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results = []
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@ -99,6 +100,8 @@ if __name__ == "__main__":
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jobs.append(last_step)
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array_mean_timings = load_array_mean_timings(jobid, excluded_array_indices)
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if args.dump_timings:
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print(array_mean_timings, file=sys.stderr)
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results.append({
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"jobid": jobid,
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63
experiments/eval/strong-booster.json
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63
experiments/eval/strong-booster.json
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{
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"common": {
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"account": "hkf6",
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"partition": "booster",
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"extra_sbatch_line": "#SBATCH --gres=gpu:4",
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"logfile_path": "/p/project/cellsinsilico/paulslustigebude/ma/experiments/eval/logs/%x-%A.%a",
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"nastja_binary_path": "/p/project/cellsinsilico/paulslustigebude/nastja/build-cuda/nastja",
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"config_path": "/p/project/cellsinsilico/paulslustigebude/ma/experiments/eval/generated/config/${SLURM_JOB_NAME}.json",
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"output_dir_path": "/p/scratch/cellsinsilico/paul/nastja-out/${SLURM_JOB_NAME}-${SLURM_ARRAY_JOB_ID}.${SLURM_ARRAY_TASK_ID}"
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},
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"batches": [
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{
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"name": "strong-booster-01-01-01",
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"nodes": 1,
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"tasks": 1,
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"time": "00:15:00",
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"extra_sbatch_line": "#SBATCH --gres=gpu:1"
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},
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{
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"name": "strong-booster-01-01-02",
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"nodes": 1,
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"tasks": 2,
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"time": "00:15:00",
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"extra_sbatch_line": "#SBATCH --gres=gpu:2"
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},
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{
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"name": "strong-booster-01-02-02",
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"nodes": 1,
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"tasks": 4,
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"time": "00:15:00"
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},
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{
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"name": "strong-booster-02-02-02",
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"nodes": 2,
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"tasks": 8,
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"time": "00:15:00"
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},
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{
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"name": "strong-booster-02-02-04",
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"nodes": 4,
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"tasks": 16,
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"time": "00:15:00"
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},
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{
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"name": "strong-booster-02-04-04",
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"nodes": 8,
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"tasks": 32,
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"time": "00:15:00"
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},
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{
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"name": "strong-booster-04-04-04",
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"nodes": 16,
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"tasks": 64,
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"time": "00:15:00"
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},
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{
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"name": "strong-booster-04-04-08",
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"nodes": 32,
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"tasks": 128,
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"time": "00:15:00"
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}
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]
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}
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263
experiments/eval/templates/strong-booster.json
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263
experiments/eval/templates/strong-booster.json
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{
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"Application": "Cells",
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"CellsInSilico": {
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"2D": false,
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"adhesion": {
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"matrix": [
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[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
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[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 450.0],
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[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
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[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
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[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
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[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
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[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
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[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
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[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
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[0.0, 450.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 50.0]
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],
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"polarityenabled": false
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},
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"centerofmass": {
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"steps": 1
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},
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"cleaner": {
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"killdistance": 0,
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"steps": 100
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},
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"contactinhibition": {
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"enabled": false
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},
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"division": {
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"condition": [
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"",
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"",
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"",
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"",
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"",
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"",
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"",
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"",
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"",
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"( volume >= 0.9 * volume0 ) & ( rnd() <= 0.00001 ) & generation < 1"
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],
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"enabled": true,
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"halveSignals": false
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},
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"dynamicecm": {
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"alpha": 2.0,
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"beta": 0.5,
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"c": 4.0,
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"deltat": 0.10000000149011612,
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"ecmCellID": 0,
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"enabled": true,
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"eta": 0.25,
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"k0": 0.10000000149011612,
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"k1": 0.10000000149011612,
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"lambda": 10.0,
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"phi": 1.0,
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"pushSteps": 10,
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"pushWeight": 0.5,
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"stepsPerMcs": 100
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},
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"ecmdegradation": {
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"enabled": false
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},
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"energyfunctions": [
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"Volume00",
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"Surface01",
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"Motility00",
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"Adhesion01",
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"DynamicECM00"
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],
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"liquid": 6,
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"logcellproperties": {
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"enabled": false
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},
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"orientation": {
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"enabled": true,
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"motility": "persistentRandomWalk",
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"motilityamount": [
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0
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],
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"numRandomNumbers": 5,
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"persistenceMagnitude": 0.0,
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"persistentDecay": 0.8,
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"recalculationtime": 200
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},
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"polarity": {
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"enabled": false
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},
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"signaling": {
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"constant": false,
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"enabled": false
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},
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"surface": {
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"default": {
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"storage": "const",
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"value": 400.0
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},
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"lambda": [
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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5.625,
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5.625,
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1.0
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],
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"sizechange": [
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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-0.05,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0
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]
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},
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"temperature": 50.0,
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"visitor": {
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"checkerboard": "01",
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"stepwidth": 10
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},
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"volume": {
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"default": {
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"storage": "const",
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"value": 500.0
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},
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"lambda": [
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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7.5,
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7.5,
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7.5
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],
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"sizechange": [
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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-0.05,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0,
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0.0
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]
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}
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},
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"DefineFunctions": [
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"r_angle()=360*rnd()",
|
||||
"r_size()=400*rnd()"
|
||||
],
|
||||
"Filling": {
|
||||
"cells": [
|
||||
{
|
||||
"box": [
|
||||
[
|
||||
0,
|
||||
0,
|
||||
0
|
||||
],
|
||||
[
|
||||
384,
|
||||
384,
|
||||
384
|
||||
]
|
||||
],
|
||||
"celltype": 0,
|
||||
"component": 0,
|
||||
"pattern": "const",
|
||||
"seed": 0,
|
||||
"shape": "cube",
|
||||
"value": 0
|
||||
},
|
||||
{
|
||||
"box": [
|
||||
[117, 117, 177],
|
||||
[267, 267, 267]
|
||||
],
|
||||
"celltype": 9,
|
||||
"center": [192, 192, 192],
|
||||
"component": 0,
|
||||
"count": 5500,
|
||||
"pattern": "voronoi",
|
||||
"radius": 75,
|
||||
"seed": 758960,
|
||||
"shape": "sphere",
|
||||
"value": 8
|
||||
}
|
||||
],
|
||||
"initialoutput": false,
|
||||
"randomseed": 758959
|
||||
},
|
||||
"Geometry": {
|
||||
"blockcount": [
|
||||
4,
|
||||
4,
|
||||
3
|
||||
],
|
||||
"blockdefault": "fill",
|
||||
"blocksize": [
|
||||
96,
|
||||
96,
|
||||
128
|
||||
],
|
||||
"blocktype": [
|
||||
[
|
||||
[
|
||||
1
|
||||
]
|
||||
]
|
||||
]
|
||||
},
|
||||
"Settings": {
|
||||
"deltat": 1.0,
|
||||
"deltax": 1.0,
|
||||
"handleFPE": "signal",
|
||||
"logger": {
|
||||
"group": 0,
|
||||
"steps": 100
|
||||
},
|
||||
"randomseed": 42,
|
||||
"statusoutput": 1,
|
||||
"timestepguard": 1,
|
||||
"timesteps": 10,
|
||||
"cuda": {
|
||||
"subblocks": {
|
||||
"blockDim": [8, 8, 8]
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
Loading…
x
Reference in New Issue
Block a user