Scalable Coarse Grained Parallel Interval Graph Algorithms

We present scalable coarse grained parallel algorithms for solving interval graph problems on a BSP-like model{Coarse Grained Multicomputers (CGM). The problems we consider include: nding maximum independent set, maximum weighted clique, minimum coloring and cut vertices and bridges. With scalability at n p p ; 8 > 0 (here n denotes the total input size and p the number of processors), our algorithms for maximum independent set and minimum coloring use optimal computation time and O(log p) communication rounds, which is independent of the input size and grows slowly only with the number of processors. Equally scalable are our algorithms for nding maximum weighted clique, cut vertices and bridges, which use O(1) communication rounds and optimal local computation time, achieving both communication and computation optimality.