https://github.com/tsudalab/dp-chemts

A distributed framework based on Monte Carlo tree search for accelerating molecular discovery.
https://github.com/tsudalab/dp-chemts

Last synced: about 1 month ago
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A distributed framework based on Monte Carlo tree search for accelerating molecular discovery.

• Host: GitHub
• URL: https://github.com/tsudalab/dp-chemts
• Owner: tsudalab
• Created: 2018-01-15T03:38:39.000Z (almost 7 years ago)
• Default Branch: master
• Last Pushed: 2018-03-20T13:35:51.000Z (almost 7 years ago)
• Last Synced: 2023-10-20T23:33:29.517Z (about 1 year ago)
• Language: Python
• Size: 9.01 MB
• Stars: 12
• Watchers: 8
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# DP-ChemTS

A distributed framework based on Monte Carlo tree search for accelerating molecular discovery. DP-ChemTS is the distributed parallel version of our publish ChemTS library. DP-ChemTS implemented three distributed parallel methods: Distributed leaf parallel, distributed tree parallel and distributed tree parallel with virtual loss(is used to reduce the search overhead). 

# Requirements

1.mpi4py

2.MPICH

3.Cluster machines

4. Other requirements for ChemTS.

# How to use DP-ChemTS?

1. Distributed leaf parallel.

cd leaf_parallel_test/simulation1/4core

run: mpiexec -n 4 python mpi_thread_leaf_parallel.py

2. Distributed tree parallel.

cd tree_parallel_test/simulation1/4core

run: mpiexec -n 4 python mpi_thread_chemts_tree_parallel.py

3. Distributed tree parallel with virtual loss.

cd virtual_loss_test/simulation1/4core

run: mpiexec -n 4 python mpi_thread_chemts_tree_vl.py