Towards Massively Parallel Local Search for SAT
Parallel portfolio-based algorithms have become a standard methodology for building parallel algorithms for SAT. In this methodology, different algorithms (or the same one with different random seeds) compete to solve a given problem instance. Moreover, the portfolio is usually equipped with cooperation, this way algorithms exchange important knowledge acquired during the search to solve a given problem instance. Portfolio algorithms based on complete solvers exchange learned clauses which are incorporated within each search engine (e.g. ManySAT  and plingeling), while those based on incomplete solvers  exchange the best assignment for the variables found so far in order to properly craft a new assignment for the variables to restart from. These strategies range from a voting mechanism where each algorithm in the portfolio suggests a value for each variable to probabilistic constructions.