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SLIME CLI & SLIME CLOUD
Currently the best SAT Solver, several light years around.
SLIME CLI
Kissat-sc2020 vs SLIME 5 at 10.000 seconds
Anonymous Link to Report
SLIME 5
PAR-2 Score 1499518.553
Solved 192 = SAT 131 + UNSAT 61
Kissat-sc2020: http://fmv.jku.at/kissat/
PAR-2 Score 1564281.3671
Solved 185 = SAT 115 + UNSAT 71
SLIME 5 Cloud: A Free Massive World Class High Performance SAT Solver.
- SLIME 5, binary distribution, single node compilation.
- https://github.com/maxtuno/slime-sat-solver/tree/master/SLIME5-binary
- SLIME 4 win 3rd place on Cloud Track from SAT Competition 2020 https://satcompetition.github.io/2020/index.html.
SLIME 5: The Unofficial State of The Art
- SLIME vs The Winner of the SAT Competition 2020 Main Track.
SLIME 3.1.1: The Unofficial State of The Art
- SLIME vs The Winners of the SAT Race 2019.
SLIME 3.1: The Unofficial State of The Art
- Support long term executions without overflow on counters and variables.
- The State of The Art Performance.
SLIME 3.0: The Unofficial State of The Art
- Implementation of Alternating Dual BOOST Heuristic.
- The State of The Art Performance.
SLIME 2.2: A Free World Class Multiplatform High Performance SAT Solver
- Windows support - include a precompiled executable
- usage: slime_cli cnf-file [sat-model-file] [unsat-proof-file]
- 2.0 performance
SLIME 2.1: A Free World Class High Performance SAT Solver
- Full ANSI C++
- Remove ZLib dependency
- Extreme simplification of unused components
- 2.0 performance
- More compatibility with all OS. (Full Raspbian Compatibility)
SLIME 2.0: A Free World Class High Performance SAT Solver
SAT Race 2015
- v1.0 PAR-2 605079.2646
- v2.0 PAR-2 591812.0663
(The solvers will ranked using the PAR-2 scheme: The score of a solver is defined as the sum of all runtimes for solved instances + 2*timeout for unsolved instances, lowest score wins.)
SLIME: A Minimal Heuristic to Boost SAT Solving
On CDCL Based SAT Solvers the trail size is strictly related to progress or to the total conflicts on the current assignment,
such that if the trail size is the same that the number of variables, then current assignment is valid.
On the other hand, in the selection of the current variable it is necessary to assign a predetermined polarity to the resulting literal, which in most implementations is a predefined value.
SLIME implement a simple heuristic with minimal complexity, that correlated the trail size and the polarity of the current variable to assign.
The selection of variable is not related to trail size, this decouple the both concepts.