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fix sponge readme
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SPONGE in MindSpore is a high-performance and modularized molecular dynamics simulation library developed by `Yiqin Gao` group (`Peking University` and `Shenzhen Bay Laboratory`) and `MindSpore` team at `Huawei` Company. It can efficiently simulate traditional molecular dynamics tasks based on the “graph-kernel-fusion” and “automatic parallelization” features of MindSpore. In the meanwhile, it utilizes the automatic differentiation feature of MindSpore, and introduces machine learning methods, such as neural network, into traditional molecular simulation, achieving methodological inventions.
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This example demonstrates how to perform high-performance molecular dynamics simulations with the built-in SPONGE module of MindSpore on GPU.
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This example demonstrates how to perform high-performance molecular dynamics simulations with the built-in SPONGE module of MindSpore on `GPU`.
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## Dataset
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There are three inputs for the example, property file `NVT_290_10ns.in`, topology file `ala.parm7` and coordinates file `ala_NVT_290_10ns.out`, respectivelly.
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There are three inputs for the example, property file `NVT_290_10ns.in`, topology file `WATER_ALA.parm7` and coordinates file `WATER_ALA_350_cool_290.rst7`, respectivelly.
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![ALA Aqueous System](https://images.gitee.com/uploads/images/2021/0323/184453_4bd9b1a6_8142020.png "图片1.png")
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@ -30,8 +30,8 @@ Topology file and coordinates file can be generated by `tleap` in `AmberTools` (
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## Environment Requirements
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- Hardware: GPU
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- Prepare hardware environment with GPU processor.
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- Hardware: `GPU`
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- Prepare hardware environment with `GPU` processor.
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- Framework
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- [MindSpore](https://www.mindspore.cn/install/en)
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- For more information, please check the resources below:
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After installing MindSpore via the official website, you can start running as follows:
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```shell
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python main.py --i /path/NVT_290_10ns.in --amber_parm /path/ala.parm7 --c /path/ala_350_cool_290.rst7 \
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python main.py --i /path/NVT_290_10ns.in \
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--amber_parm /path/WATER_ALA.parm7 \
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--c /path/WATER_ALA_350_cool_290.rst7 \
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--o /path/ala_NVT_290_10ns.out
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```
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@ -67,13 +69,16 @@ python main.py --i /path/NVT_290_10ns.in --amber_parm /path/ala.parm7 --c /path/
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├── md_information.py # save md information module in SPONGE
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├── neighbor_list.py # neighbor_list module in SPONGE
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├── particle_mesh_ewald.py # particle_mesh_ewald module in SPONGE
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├── simulation_initial.py # SPONGE simulation
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├── simulation.py # SPONGE simulation
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```
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### Training Process
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```shell
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python main.py --i ./NVT_290_10ns.in --amber_parm ala.parm7 --c ala_350_cool_290.rst7 --o ala_NVT_290_10ns.out
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python main.py --i /path/NVT_290_10ns.in \
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--amber_parm /path/WATER_ALA.parm7 \
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--c /path/WATER_ALA_350_cool_290.rst7 \
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--o /path/ala_NVT_290_10ns.out
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```
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Training result will be stored in the specified file, which ends with ".out".
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@ -101,8 +106,8 @@ There are sorts of energy in the output, steps (_steps_), temperature (_TEMP_),
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| MindSpore Version | 1.2
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| Training Parameters | step=1
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| Outputs | numpy file
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| Speed | 0.47 s/step
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| Total time | 4.57 s
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| Speed | 16.7 ms/step
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| Total time | 10.7 s
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| Scripts | [Link](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/hpc/sponge)
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## ModelZoo HomePage
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