Showing papers on "Binary heap published in 1992"
TL;DR: This work describes a new parallel data structure, namely parallel heap, for exclusive-read exclusive-write parallel random access machines, which is the first such data structure to efficiently implement a truly parallel priority queue based on a heap structure.
Abstract: We describe a new parallel data structure, namely parallel heap, for exclusive-read exclusive-write parallel random access machines. To our knowledge, it is the first such data structure to efficiently implement a truly parallel priority queue based on a heap structure. Employing p processors, the parallel heap allows deletions of θ(p) highest priority items and insertions of θ(p) new items, each in O(log n) time, where n is the size of the parallel heap. Furthermore, it can efficiently utilize processors in the range 1 through n.
72 citations
29 Jun 1992
TL;DR: A linear-time, constant-space algorithm to construct a binary heap whose inorder traversal equals a given sequence and is derived in terms of binary trees.
Abstract: In this paper we derive a linear-time, constant-space algorithm to construct a binary heap whose inorder traversal equals a given sequence. We do so in two steps. First, we invert a program that computes the inorder traversal of a binary heap, using the proof rules for program inversion by W. Chen and J.T. Udding. This results in a linear-time solution in terms of binary trees. Subsequently, we data-refine this program to a constant-space solution in terms of linked structures.
14 citations
TL;DR: Results indicate that the two recently introduced self-adjusting heaps are the most competitive choices for the applications considered, and there are strong grounds for believing the conjectured amortized time bounds for pairing heap operations.
Abstract: Results indicate that the two recently introduced self-adjusting heaps are the most competitive choices for the applications considered. Further, the results indicate that only some heap structures support lazymerge/lazydelete operations well, partially confirming that algorithms based on top-down skew heap compare more favorably than those based on binomial queues, that there are strong grounds for believing the conjectured amortized time bounds for pairing heap operations, and that pairing heaps are a competitive alternative to Fibonacci heaps.
13 citations
08 Jul 1992
TL;DR: It is shown how to put n values into heap order in O(log log n) time using n/ log log n processors in the parallel comparison tree model of computation, and in O (α(n)) time on n/ α(n) processors, in the randomized parallel comparison Tree model, where α( n) is an inverse of Ackerman's function.
Abstract: I show how to put n values into heap order in O(log log n) time using n/ log log n processors in the parallel comparison tree model of computation, and in O(α(n)) time on n/α(n) processors, in the randomized parallel comparison tree model, where α(n) is an inverse of Ackerman's function. I prove similar bounds for the related problem of putting n values into a min-max heap.
11 citations
29 Jun 1992
5 citations
23 Mar 1992
TL;DR: This version of the data structure parallel heap does not require dedicated maintenance processors, and performs insertion and deletion in place, and can efficiently utilize processors in the range 1 through n.
Abstract: Describes a new updated version of the data structure parallel heap. Employing p processors, a parallel heap allows detections of Theta (p) highest-priority items and insertion of Theta (p) new items each in O(logn) time on an EREW PRAM where n is the size of the parallel heap. Furthermore, it can efficiently utilize processors in the range 1 through n. This version does not require dedicated maintenance processors, and performs insertion and deletion in place. >
4 citations
TL;DR: This work studies parallel solutions to the problem of implementing priority queues and priority deques by designing and implementing parallel data structures for the implementation of heap hierarchies.
Abstract: We study parallel solutions to the problem of implementing priority queues and priority deques. It is known that data structures for the implementation (e.g. the heap, the min-max heap, and the dea...
2 citations
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TL;DR: New designs for performing a group of priority queue operations on a set of elements are presented, called the banyan heap machine, which requires fewer processors to meet the same capacity requirement, and also, processors do not have geometrically varying memory sizes.
Abstract: New designs for performing a group of priority queue operations on a set of elements are presented. Processors in this design, called the banyan heap machine are connected together to form a linear chain. The algorithms for the banyan heap machine are the generalization of binary heap algorithms to a more general acyclic graph called banyan. This design, unlike existing designs, requires fewer processors to meet the same capacity requirement, and also, processors do not have geometrically varying memory sizes. This results in a completely homogeneous system. The key advantage of the banyan heap machine is in its ability to retrieve elements at different percentile levels. >
1 citations
01 Jan 1992
TL;DR: Results indicate that the two recently introduced self-adjusting heaps are the most competitive choices for the applications considered, and there are strong grounds for believing the conjectured amortized time bounds for pairing heap operations.
Abstract: Results indicate that the two recently introduced self-adjusting heaps are the most competitive choices for the applications considered. Further, the results indicate that only some heap structures support lazymerge/lazydelete operations well, partially confirming that algorithms based on top-down skew heap compare more favorably than those based on binomial queues, that there are strong grounds for believing the conjectured amortized time bounds for pairing heap operations, and that pairing heaps are a competitive alternative to Fibonacci heaps.