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A Parallel Priority Queue with Constant Time Operations
 JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
, 1998
"... We present a parallel priority queue that supports the following operations in constant time: parallel insertion of a sequence of elements ordered according to key, parallel decrease key for a sequence of elements ordered according to key, deletion of the minimum key element, as well as deletion ..."
Abstract

Cited by 15 (1 self)
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We present a parallel priority queue that supports the following operations in constant time: parallel insertion of a sequence of elements ordered according to key, parallel decrease key for a sequence of elements ordered according to key, deletion of the minimum key element, as well as deletion of an arbitrary element. Our data structure is the first to support multi insertion and multi decrease key in constant time. The priority queue can be implemented on the EREW PRAM, and can perform any sequence of n operations in O(n) time and O(m log n) work, m being the total number of keys inserted and/or updated. A main application is a parallel implementation of Dijkstra's algorithm for the singlesource shortest path problem, which runs in O(n) time and O(m log n) work on a CREW PRAM on graphs with n vertices and m edges. This is a logarithmic factor improvement in the running time compared with previous approaches.
Fast Meldable Priority Queues
, 1995
"... We present priority queues that support the operations MakeQueue, FindMin, Insert and Meld in worst case time O(1) and Delete and DeleteMin in worst case time O(log n). They can be implemented on the pointer machine and require linear space. The time bounds are optimal for all implementations wh ..."
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Cited by 11 (2 self)
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We present priority queues that support the operations MakeQueue, FindMin, Insert and Meld in worst case time O(1) and Delete and DeleteMin in worst case time O(log n). They can be implemented on the pointer machine and require linear space. The time bounds are optimal for all implementations where Meld takes worst case time o(n).
Functional Pearls: Explaining Binomial Heaps
, 1999
"... This paper explains binomial heaps, a beautiful data structure for priority queues, using the functional programming language Haskell (Peterson & Hammond, 1997). We largely follow a deductive approach: using the metaphor of a tennis tournament we show that binomial heaps arise naturally through a nu ..."
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Cited by 5 (4 self)
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This paper explains binomial heaps, a beautiful data structure for priority queues, using the functional programming language Haskell (Peterson & Hammond, 1997). We largely follow a deductive approach: using the metaphor of a tennis tournament we show that binomial heaps arise naturally through a number of logical steps. Haskell supports the deductive style of presentation very well: new types are introduced at ease, algorithms can be expressed clearly and succinctly, and Haskell's type classes allow to capture common algorithmic patterns. The paper aims at the level of an undergraduate student who has experience in reading and writing Haskell programs, and who is familiar with the concept of a priority queue. 2 Priority queues
A Generalization of Binomial Queues
 Information Processing Letters
, 1996
"... We give a generalization of binomial queues involving an arbitrary sequence (mk )k=0;1;2;::: of integers greater than one. Different sequences lead to different worst case bounds for the priority queue operations, allowing the user to adapt the data structure to the needs of a specific application. ..."
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Cited by 2 (0 self)
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We give a generalization of binomial queues involving an arbitrary sequence (mk )k=0;1;2;::: of integers greater than one. Different sequences lead to different worst case bounds for the priority queue operations, allowing the user to adapt the data structure to the needs of a specific application. Examples include the first priority queue to combine a sublogarithmic worst case bound for Meld with a sublinear worst case bound for Delete min. Keywords: Data structures; Meldable priority queues. 1 Introduction The binomial queue, introduced in 1978 by Vuillemin [14], is a data structure for meldable priority queues. In meldable priority queues, the basic operations are insertion of a new item into a queue, deletion of the item having minimum key in a queue, and melding of two queues into a single queue. The binomial queue is one of many data structures which support these operations at a worst case cost of O(logn) for a queue of n items. Theoretical [2] and empirical [9] evidence i...