https://github.com/marinoandrea/parallel-sudoku

Parallel sudoku solver, computes every legal solution for a given grid.
https://github.com/marinoandrea/parallel-sudoku

backtracking fork-join java multicore parallelism parallelization speedup sudoku sudoku-solver

Last synced: about 1 year ago
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Parallel sudoku solver, computes every legal solution for a given grid.

• Host: GitHub
• URL: https://github.com/marinoandrea/parallel-sudoku
• Owner: marinoandrea
• Created: 2019-06-11T11:03:21.000Z (about 7 years ago)
• Default Branch: master
• Last Pushed: 2019-06-11T11:04:10.000Z (about 7 years ago)
• Last Synced: 2025-01-24T08:43:54.511Z (over 1 year ago)
• Topics: backtracking, fork-join, java, multicore, parallelism, parallelization, speedup, sudoku, sudoku-solver
• Language: Java
• Size: 115 KB
• Stars: 0
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Parallel Sudoku

This is a java implementation of a parallel sudoku solver (it computes every possible solution) based on the fork-join paradigm. It also includes a sequential backtracking implementation in order to make benchmarking and speed-up analysis possible.

The program takes text files representing a sudoku grid as input:

    .....2...

    ..4...75.

    73.9..6..

    3.5..8...

    .6.1...85

    ..92.....

    .9..4.26.

    2.....17.

    ...3.....

And outputs in the following order:

- The solution space

- The completion percentage of the input grid

- The number of possible solutions to the sudoku

Some benchmark graphs:

![Execution time vs Solution space](/benchmarks/time_space.png)

![Speedup vs Number of processors](/benchmarks/speedup.png)

# Usage

Compile the main class as follows:

    javac Sudoku.java

Run any test by passing a text file in the specified format as parameter:

    java Sudoku $(PATH_TO_FILE)

Or use the grader.sh bash script to test the algorithm on any file present in the tests folder:

    ./grader.sh

# Features

- Fork-Join parallelization

- Sequential cutoff optimization

- Thread-halving optimization

- Bit masks optimization on candidates selection