# Parallel project notes We track notes for updates to smt\_parallel.cpp and possibly solver/parallel\_tactic.cpp ## Variable selection heuristics * Lookahead solvers: * lookahead in the smt directory performs a simplistic lookahead search using unit propagation. * lookahead in the sat directory uses custom lookahead solver. They both proxy on a cost model where the most useful variable to branch on is the one that _minimizes_ the set of new clauses maximally through unit propagation. In other words, if a literal _p_ is set to true, and _p_ occurs in clause $\neg p \vee q \vee r$, then it results in reducing the clause from size 3 to 2 (because $\neg p$ will be false after propagating _p_). * VSIDS: * As referenced in Matteo and Antti's solvers. * Variable activity is a proxy for how useful it is to case split on a variable during search. Variables with a higher VSIDS are split first. * VSIDS is updated dynamically during search. It was introduced in the paper with Moscovitz, Malik, et al in early 2000s. A good overview is in Armin's tutorial slides (also in my overview of SMT). * VSIDS does not keep track of variable phases (if the variable was set to true or false). * Proof prefix: * Collect the literals that occur in learned clauses. Count their occurrences based on polarity. This gets tracked in a weighted score. * The weight function can be formulated to take into account clause sizes. * The score assignment may also decay similar to VSIDS. * We could also use a doubly linked list for literals used in conflicts and keep reinsert literals into the list when they are used. This would be a "Variable move to front" (VMTF) variant. * From local search: * Note also that local search solvers can be used to assign variable branch priorities. * We are not going to directly run a local search solver in the mix up front, but let us consider this heuristic for completeness. * The heuristic is documented in Biere and Cai's journal paper on integrating local search for CDCL. * Roughly, it considers clauses that move from the UNSAT set to the SAT set of clauses. It then keeps track of the literals involved. * Assignment trails: * We could also consider the assignments to variables during search. * Variables that are always assigned to the same truth value could be considered to be safe to assign that truth value. * The cubes resulting from such variables might be a direction towards finding satisfying solutions. ## Algorithms This section considers various possible algorithms. In the following, $F$ refers to the original goal, $T$ is the number of CPU cores or CPU threads. ### Base algorithm The existing algorithm in smt_parallel is as follows: 1. Run a solver on $F$ with a bounded number of conflicts. 2. If the result is SAT/UNSAT, or UNKNOWN with an interrupt or timeout, return. If the maximal number of conflicts were reached continue. 3. Spawn $T$ solvers on $F$ with a bounded number of conflicts, wait until a thread returns UNSAT/SAT or all threads have reached a maximal number of conflicts. 4. Perform a similar check as in 2. 5. Share unit literals learned by each thread. 6. Compute unit cubes for each thread $T$. 7. Spawn $T$ solvers with $F \wedge \ell$, where $\ell$ is a unit literal determined by lookahead function in each thread. 8. Perform a similar check as in 2. But note that a thread can be UNSAT because the unit cube $\ell$ contradicted $F$. In this case learn the unit literal $\neg \ell$. 9. Shared unit literals learned by each thread, increase the maximal number of conflicts, go to 3. ### Algorithm Variants * Instead of using lookahead solving to find unit cubes use the proof-prefix based scoring function. * Instead of using independent unit cubes, perform a systematic (where systematic can mean many things) cube and conquer strategy. * Change the synchronization barrier discipline. * [Future] Include in-processing