An efficient data structure for dynamic memory management
Journal of Systems and Software
ACM Computing Surveys (CSUR)
New Connectivity and MSF Algorithms for Shuffle-Exchange Network and PRAM
IEEE Transactions on Computers
Efficient parallel algorithms for path problems in directed graphs
SPAA '89 Proceedings of the first annual ACM symposium on Parallel algorithms and architectures
An efficient and fast parallel-connected component algorithm
Journal of the ACM (JACM)
On the number of minimum size separating vertex sets in a graph and how to find all of them
SODA '90 Proceedings of the first annual ACM-SIAM symposium on Discrete algorithms
Parallel permutation and sorting algorithms and a new generalized connection network
Journal of the ACM (JACM)
Journal of the ACM (JACM)
ACM Transactions on Programming Languages and Systems (TOPLAS)
Efficient parallel algorithms for some graph problems
Communications of the ACM
Fast parallel sorting algorithms
Communications of the ACM
Proceedings of the 11th international conference on World Wide Web
STOC '82 Proceedings of the fourteenth annual ACM symposium on Theory of computing
Parallelism in random access machines
STOC '78 Proceedings of the tenth annual ACM symposium on Theory of computing
Utilisation du parallelisme en traduction automatisee par ordinateur
COLING '82 Proceedings of the 9th conference on Computational linguistics - Volume 1
On the parallel computation of the biconnected and strongly connected co-components of graphs
Discrete Applied Mathematics
Binary Trees and Parallel Scheduling Algorithms
IEEE Transactions on Computers
Hirschberg's algorithm on a GCA and its parallel hardware implementation
Euro-Par'07 Proceedings of the 13th international Euro-Par conference on Parallel Processing
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Parallel programs are presented that determine the transitive closure of a matrix using n3 processors and connected components of an undirected graph using n2 processors. In both cases, the desired results are obtained in time 0(log2n). It is assumed that the processors have access to common memory. Simultaneous access to the same location is permitted for fetch, but not store, instructions. The problem of determining the connected components of a graph using a parallel computer has recently appeared in the literature [1,2]. The result in [1] is based on finding the transitive closure of a matrix in time 0(log2n) which can be done using 0(n3) processors. We show that n2 processors are sufficient to solve the connected component problem in time 0(log2n). We present algorithm CLOSURE that will find the transitive closure of Boolean matrix M [n by n] using n3 processors [numbered P(0,0,0) through P(n−1 ,n−1, n−1)] each of which has local memory and each of which can access common array A [n by n].