AbstractThis paper describes unification algorithms for fine-grained massively parallel computers. The algorithms are based on a parallel marker-passing scheme. The marker-passing scheme in our algorithms carry only bit-vectors, address pointers and values. Because of their simplicity, our algorithms can be implemented on various architectures of massively parallel machines without loosing the inherent benefits of parallel computation. Also, we describe two augmentations of unification algorithms such as multiple unification and fuzzy unification. Experimental results indicate that our algorithm attaines more than 500 unification per seconds (for DAGs of average depth of 4) and has a linear time-complexity. This leads to possible implementations of massively parallel natural language parsing with full linguistic analysis.