https://github.com/mithaystack/cuda_mcmc
https://github.com/mithaystack/cuda_mcmc
Last synced: 11 months ago
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- Host: GitHub
- URL: https://github.com/mithaystack/cuda_mcmc
- Owner: MITHaystack
- Created: 2019-03-01T15:44:35.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2019-04-05T21:16:01.000Z (almost 7 years ago)
- Last Synced: 2025-01-05T22:42:20.289Z (about 1 year ago)
- Language: Python
- Homepage:
- Size: 2 MB
- Stars: 1
- Watchers: 5
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# cuda_mcmc
The cuda_mcmc software is designed to greatly accelerate solving various optimization problems using the NVIDIA graphics processing units (GPU) with the CUDA computing platform. We use a version of the Markov chain Monte-Carlo (MCMC) algorithm based on the Metropolis-Hastings sampler with replica exchange (MCMC-RE). The detailed description of the algorithm with its mapping on the CUDA GPU architecture including the user instructions to its installation and writing custom optimization/equation solving applications is provided in the `doc/` directory. Several examples of the code usage are given in the `examples/` directory.
To start using CUDA MCMC software, first enter its containing directory (usually `~/cuda_mcmc`) and issue the
command
$ make
It will create the directories `~/lib64/python`, and `~/bin`, and setup the
environment for them by adding to the end of the `~/.bashrc` file the lines
export PATH=$PATH:~/bin
export PYTHONPATH=$PYTHONPATH:~/lib64/python
After `make` finishes, update the environment variables PATH and PYTHONPATH issuing the command
$ source ~/.bashrc
Or simply open a new console window. This will automatically run ~/.bashrc
script and set the environment variables.