Course ContentsReview of important sequential graph algorithms.Introduction to parallel models for computation. General techniques for fast parallel computations on vectors and lists and their applications to design of efficient parallel graph algorithms. Parallel dynamic programming and its applications to expression graphs. State-of-art algorithms for depth first search of directed and undirected agraphs. NC-algorithms for st-numbering and open ear decomposition. Parallel algorithms for graph optimization problems. Algorithms for graph coloring. Decomposition of graph into simpler subgraphs. Equivalence relations and classes in graphs. Parallel planarity testing. Books and References:
Evaluation:x+x Mid sem2x End Sem with (22 % <= x <= 22.5%) Total Weightage of Exams : 88% -90% Attendance 10% Quizzes/Assignment etc.(max 2%) |