https://github.com/compdyn/rl_grid_coarsen
Science Score: 10.0%
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○CITATION.cff file
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○codemeta.json file
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✓Academic publication links
Links to: arxiv.org -
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○Scientific vocabulary similarity
Low similarity (4.4%) to scientific vocabulary
Last synced: 10 months ago
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Repository
Basic Info
- Host: GitHub
- Owner: compdyn
- License: mit
- Language: Python
- Default Branch: main
- Size: 74.2 KB
Statistics
- Stars: 5
- Watchers: 2
- Forks: 4
- Open Issues: 0
- Releases: 0
Created about 5 years ago
· Last pushed over 4 years ago
https://github.com/compdyn/rl_grid_coarsen/blob/main/
# Optimization-Based Algebraic Multigrid Coarsening Using Reinforcement Learning (NeurIPS 2021) Code for reproducing the experimental results of our paper: https://arxiv.org/pdf/2106.01854.pdf ## Requirements * Python = 3.8.10 * PyTorch = 1.9.0 * Pytorch_Geometric = 1.7.2 * pyamg = 4.1.0 * networkx = 2.6.2 * pygmsh = 7.1.6 * gmsh = 4.8.0 ## Training ``` python main.py ``` ## Files * Batch_Graph.py: The class for making a batch of grids to be the input to the agent's network. * DuelingNet.py: The netwrok architecture that the agent utilizes (TAGCN network). * Lloyd_Unstructured.py: The code for the generating Lloyd agregations on grids. * MG_Agent.py: The class for Dueling Double DQN agent. * Optim.py: The code for running the grid coarsinging using Lloyed aggregation. * Solve_MG.py: The code for the two grid cycle AMG algorithm. * Unstructured.py: The class for defining grids and making unstructured meshes. * fem.py: Constructs a finite element discretization of a 2D Poisson problem. * main.py: The main driver for training the RL agent and test functions.
Owner
- Name: compdyn
- Login: compdyn
- Kind: organization
- Repositories: 6
- Profile: https://github.com/compdyn