Compilers: principles, techniques, and tools
Compilers: principles, techniques, and tools
Efficient plane sweeping in parallel
SCG '86 Proceedings of the second annual symposium on Computational geometry
Relations between concurrent-write models of parallel computation
SIAM Journal on Computing
SIAM Journal on Computing
Improved deterministic parallel integer sorting
Information and Computation
An introduction to parallel algorithms
An introduction to parallel algorithms
Recursive star-tree parallel data structure
SIAM Journal on Computing
The parallel simplicity of compaction and chaining
Journal of Algorithms
Information and Computation
Finding pattern matchings for permutations
Information Processing Letters
The art of computer programming, volume 1 (3rd ed.): fundamental algorithms
The art of computer programming, volume 1 (3rd ed.): fundamental algorithms
Optimal parallel algorithms for direct dominance problems
Nordic Journal of Computing
Pattern Matching for Permutations
WADS '93 Proceedings of the Third Workshop on Algorithms and Data Structures
Incomparability in parallel computation
SFCS '87 Proceedings of the 28th Annual Symposium on Foundations of Computer Science
The Möbius function of separable and decomposable permutations
Journal of Combinatorial Theory Series A
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In this paper, it is shown that on the CREW model we can test whether a given permutation of 1,...,n is separable in O(logn) time with n processors. If d is the depth of the optimal (minimum) depth separating tree of a separable permutation, then a separating tree of depth @Q(d) can be constructed on the CREW model in O(logn) time with O(n^2) cost or alternatively in O(dlogn) time with O(nd) cost. We can test whether the given separable permutation P of 1,...,k has a match in a permutation T of 1,...,n (n=k) in O(dlogn) time with O(kn^4) cost (the same as that of the serial algorithm). We can also find the number of matches of P in T in O(dlogn) time with O(kn^6) cost (the same as that of the serial algorithm). Both algorithms are for the CREW model. We also discuss how the space complexity of the existing serial algorithms for the decision problem can be reduced from O(kn^3) to O(n^3logk) and of the counting version from O(kn^4) to O(n^4logk).