import util
import os
from IPython.core.display import Markdown
benchmark = 'dodecahedron'
Markdown(open(os.path.join(benchmark, 'README.md'), 'r').read())
The dodecahedron benchmark runs a system of $131,072$ dodecahedra using hard particle Monte Carlo. This is a synthetic benchmark of 3D convex polyhedra performance.
Parameters:
Performance results are reported in hours to complete ten million Monte Carlo sweeps, where one sweep is N trial moves.
rows = util.read_rows(benchmark)
table = util.make_table(rows)
Markdown(table)
Date | System | Compiler | CUDA | HOOMD | Precision | N | CPU | GPU | Ranks | Time for 10e6 steps (hours) |
---|---|---|---|---|---|---|---|---|---|---|
2018/01/15 | comet | gcc 4.9.2 | 8.0 | 2.2.2 | double | 131,072 | Intel(R) Xeon(R) CPU E5-2680 v4 @ 2.40GHz | Tesla P100-PCIE-16GB | 1 | 7.28 |
2016/10/23 | psg | gcc 4.8.5 | 8.0 | 2.1.1 | double | 131,072 | Intel(R) Xeon(R) CPU E5-2698 v3 @ 2.30GHz | Tesla P100-PCIE-16GB | 1 | 6.22 |
2016/10/23 | psg | gcc 4.8.5 | 8.0 | 2.1.1 | double | 131,072 | Intel(R) Xeon(R) CPU E5-2698 v3 @ 2.30GHz | Tesla M40 24GB | 1 | 17.33 |
2016/10/23 | psg | gcc 4.8.5 | 8.0 | 2.1.1 | double | 131,072 | Intel(R) Xeon(R) CPU E5-2698 v3 @ 2.30GHz | Tesla K80 | 1 | 25.66 |
2016/10/23 | psg | gcc 4.8.5 | 8.0 | 2.1.1 | double | 131,072 | Intel(R) Xeon(R) CPU E5-2698 v3 @ 2.30GHz | Tesla K40m | 1 | 30.98 |
from IPython.display import HTML
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