This paper develops new techniques for constructing separators for graphs embedded on surfaces of bounded genus. For any arbitrarily small positive " we show that any n-vertex graph G of genus g can be divided in O(n + g) time into components whose sizes do not exceed "n by removing a set C of O( p (g + 1=")n) vertices. Our result improves the best previous ones with respect to the size of C and the time complexity of the algorithm. Moreover, we show that one can cut off from G a piece of no more than (1 \Gamma ")n vertices by removing a set of O( p n"(g" + 1) vertices. Both results are optimal up to a constant factor. Keywords: graph separator, graph genus, algorithm, divide-and-conquer, topological graph theory AMS(MOS) subject classifications: 05C10, 05C85, 68R10 1 Bulgarian Academy of Sci., CICT, G.Bonchev 25-A, 1113 Sofia, Bulgaria 2 Department of Comp.Sci.,Rice University, P.O.Box 1892, Houston, Texas 77251, USA 1 Introduction Let S be a class of graphs closed under t...

Abstract not found

Abstract. Currently, there is a significant gap between the best sequential and parallel complexities of many fundamental problems related to digraph reachability. This complexity bottleneck essentially reflects a seemingly unavoidable reliance on transitive closure techniques in parallel algorithms for digraph reachability. To pinpoint the nature of the bottleneck, we de* velop a collection of polylog-time reductions among reachability problems. These reductions use only linear processors and work for general graphs. Furthermore, for planar digraphs, we give polylog-time algorithms for the following problems: (1) directed ear decomposition, (2) topological ordering, (3) digraph reachability, (4) descendent counting, and (5) depth-first search. These algorithms use only linear processors and therefore reduce the complexity to within a polylog factor of optimal.

A model is proposed that can be used to classify algorithms as inherently sequential. The model captures the internal computations of algorithms. Previous work in complexity theory has focused on the solutions algorithms compute. Direct comparison of algorithms within the framework of the model is possible. The model is useful for identifying hard to parallelize constructs that should be avoided by parallel programmers. The model's utility is demonstrated via applications to graph searching. A stack breadth-first search (BFS) algorithm is analyzed and proved inherently sequential. The proof technique used in the reduction is a new one. The result for stack BFS sharply contrasts a result showing that a queue based BFS algorithm is in NC. An NC algorithm to compute greedy depth-first search numbers in a dag is presented, and a result proving that a combination search strategy called breadth-depth search is inherently sequential is also given.

. This paper shows that for a strongly connected planar directed graph of size n, a depth-first search tree rooted a specified vertex can be computed in O(log 5 n) time using n= log n processors. Previously, for planar directed graphs that may not be strongly connected, the best depth-first search algorithm runs in O(log 10 n) time using n processors. Both algorithms run on a parallel random access machine that allows concurrent reads and concurrent writes in its shared memory, and in case of a write conflict, permits an arbitrary processor to succeed. Key words. linear-processor NC algorithms, graph separators, depth-first search, planar directed graphs, strong connectivity, bubble graphs, s-t graphs AMS(MOS) subject classification. 68Q10, 05C99 1. Introduction. Depth-first search is one of the most useful tools in graph theory [32], [4]. The depth-first search problem is the following: given a graph and a distinguished vertex, construct a tree that corresponds to performing de...