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SharpSAT-TD

DOI

Submission to model counting competition 2021 by Tuukka Korhonen and Matti Järvisalo (University of Helsinki). SharpSAT-TD is based on SharpSAT, with the main new features being the use of tree decompositions in decision heuristics, new preprocessor, and directly supporting weighted model counting.

SharpSAT-TD supports exact model counting, exact weighted model counting with arbitrary precision floats, and exact weighted model counting with doubles. See a detailed description in description.pdf.

Compiling

The external dependencies needed are the GMP library, the MPFR library, and CMAKE.

To compile and link dynamically use

./setupdev.sh

To compile and link statically use

./setupdev.sh static

The binaries sharpSAT and flow_cutter_pace17 will be copied to the bin/ directory.

Running

The currently supported input/output formats are those of Model counting competition 2021.

Example unweighted model counting: cd bin ./sharpSAT -decot 1 -decow 100 -tmpdir . -cs 3500 ../examples/track1_009.cnf

Example weighted model counting with arbitrary precision: cd bin ./sharpSAT -WE -decot 1 -decow 100 -tmpdir . -cs 3500 -prec 20 ../examples/track2_003.wcnf

Example weighted model counting with double precision: cd bin ./sharpSAT -WD -decot 1 -decow 100 -tmpdir . -cs 3500 ../examples/track2_003.wcnf

In the competition setting the value of the -decot flag was 120.

Flags

  • -decot - the number of seconds to run flowcutter to find a tree decomposition. Required. Recommended value 60-600 if running with a total time budjet of 1800-3600 seconds.
  • -tpmdir - the directory to store temporary files for running flowcutter. Required.
  • -decow - the weight of the tree decomposition in the decision heuristic. Recommended value >1 if the heuristic should care about the tree decomposition.
  • -cs - limit of the cache size. If the memory upper bound is X megabytes, then the value here should be around x/2-500.
  • -WE - enable weighted model counting with arbitrary precision.
  • -WD - enable weighted model counting with double precision.
  • -prec - the number of digits in output of weighted model counting. Does not affect the internal precision.

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