Computing in the fractal cloud: modular generic solvers for SAT and Q-SAT variants.
Abstract
Abstract geometrical computation can solve hard combinatorial problems efficiently: we showed previously how Q-SAT (the satisfiability problem of quantified boolean formulae) can be solved in bounded space and time using instance-specific signal machines and fractal parallelization. In this article, we propose an approach for constructing a particular generic machine for the same task. This machine deploies the Map/Reduce paradigm over a discrete fractal structure. Moreover our approach is modular: the machine is constructed by combining modules. In this manner, we can easily create generic machines for solving satisfiability variants, such as SAT, #SAT, MAX-SAT.
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