https://github.com/ermongroup/streamline-vi-csp
https://github.com/ermongroup/streamline-vi-csp
belief-propagation constraint-satisfaction-problem nips-2018 sat-solver satisfiability variational-inference
Last synced: 5 months ago
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- Host: GitHub
- URL: https://github.com/ermongroup/streamline-vi-csp
- Owner: ermongroup
- License: mit
- Created: 2018-10-19T00:18:26.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2018-11-27T23:56:27.000Z (almost 7 years ago)
- Last Synced: 2025-03-31T16:13:23.100Z (7 months ago)
- Topics: belief-propagation, constraint-satisfaction-problem, nips-2018, sat-solver, satisfiability, variational-inference
- Language: C
- Size: 2.32 MB
- Stars: 7
- Watchers: 6
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
Streamlined Survey Propogation
============================================
This repository provides a reference implementation for solving constraint satisfaction problems via streamlined survey propogation as described in the paper:
> Streamlining Variational Inference for Constraint Satisfaction Problems
Aditya Grover, Tudor Achim, Stefano Ermon
Advances in Neural Information Processing Systems (NeurIPS), 2018
Paper: http://arxiv.org/abs/1811.09813
## General
The codebase has been built on top of the survey propogation implementation of A. Braunstein, M. Mezard, and R. Zecchina as described in the paper "Survey propagation: an algorithm for satisfiability". It is implemented in C/C++ and tested on Ubuntu 16.04.
## Setup
To compile the binaries run the following command from the root directory
```
make all
```
This will create a binary file for `sp` in the root directory (and others which will be directly accessed by `sp`).
## Options
For a full list of options, run:
```
./sp -h
```
Key options are described below:
```
-l CSP in CNF representation (if none provided, random k-SAT instance is generated)
-k length of each clause
-n number of variables
-m number of clauses
-a clause/variable ratio
-s seed for reproducibility
-% percentage of paired disjunctions (denoted as R in the paper)
-t number of streamlining iterations (denoted as T in the paper)
-d limit on the streamlined disjunctions per variable
-p prefix path where all the generated files (cnf formula, streamlined formula etc.) are dumped
```
## Examples
Baseline *survey inspired decimation* on a random 3-SAT instance with 50,000 variables and clause to variable ratio of 4.235:
```
./sp -n50000 -a4.235 -k3 -%1 -t0 -d2 -s1
```
*Survey inspired streamlining* for the same problem instance:
```
./sp -n50000 -a4.235 -k3 -%1 -t90 -d2 -s1
```
*Survey inspired streamlining* for an arbitrary CSP accessed via the filepath `csp/1.cnf`:
```
./sp -%1 -lcsp/1.cnf -t80
```
## Citing
If you find this codebase useful in your research, please consider citing the following paper:
>@inproceedings{grover2018streamlining,
title={Streamlining Variational Inference for Constraint Satisfaction Problems},
author={Grover, Aditya and Achim, Tudor and Ermon, Stefano},
booktitle={Advances in Neural Information Processing Systems},
year={2018}}