Computational geometry: an introduction
Computational geometry: an introduction
Efficient Parallel Convex Hull Algorithms
IEEE Transactions on Computers
Cascading divide-and-conquer: a technique for designing parallel algorithms
SIAM Journal on Computing
In-place techniques for parallel convex hull algorithms (preliminary version)
SPAA '91 Proceedings of the third annual ACM symposium on Parallel algorithms and architectures
An introduction to parallel algorithms
An introduction to parallel algorithms
Parallel computational geometry
Parallel computational geometry
Efficient Geometric Algorithms on the EREW PRAM
IEEE Transactions on Parallel and Distributed Systems
Planar separators and parallel polygon triangulation
Journal of Computer and System Sciences - Special issue on selected papers presented at the 24th annual ACM symposium on the theory of computing (STOC '92)
Handbook of Theoretical Computer Science
Handbook of Theoretical Computer Science
Synthesis of Parallel Algorithms
Synthesis of Parallel Algorithms
Tight bounds on the complexity of parallel sorting
STOC '84 Proceedings of the sixteenth annual ACM symposium on Theory of computing
Lower bounds for algebraic computation trees
STOC '83 Proceedings of the fifteenth annual ACM symposium on Theory of computing
Algebraic cell decomposition in NC
SFCS '85 Proceedings of the 26th Annual Symposium on Foundations of Computer Science
SFCS '86 Proceedings of the 27th Annual Symposium on Foundations of Computer Science
Parallel algorithms for higher-dimensional convex hulls
SFCS '94 Proceedings of the 35th Annual Symposium on Foundations of Computer Science
One Tool for Building Visual Models
CSSIM '09 Proceedings of the 2009 International Conference on Computational Intelligence, Modelling and Simulation
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An efficient approach to the accurate computer modeling of phenomena and processes is discussed. The "divide-and-conquer" technique is used to develop a generalized parallel-recursive algorithm for simultaneous solution of a collection of interrelated problems that use a common unified data structure (weighted concatenable queue) at the merge stage. The decomposition stage is common and is executed only once for all tasks. These means are efficient and convenient for constructing and studying complex computational models.