Book Chapter10.1007/3-540-55706-7_12
Parallel Algorithms for Priority Queue Operations
Maria Cristina Pinotti,Geppino Pucci +1 more
- 08 Jul 1992
- pp 130-139
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TL;DR: The given algorithms for insertion and deletion achieve the best possible running time for any number of processors p, with p ∈ O(log n/log log n), while the MH construction algorithm employs up to Θ(n/log n) processors optimally.
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Abstract: This paper presents parallel algorithms for priority queue operations on a p-processor EREW-PRAM. The algorithms are based on a new data structure, the Min-path Heap (MH), which is obtained as an extension of the traditional binary-heap organization. Using an MH, it is shown that insertion of a new item or deletion of the smallest item from a priority queue of n elements can be performed in O log n/p + log log n) parallel time, while construction of an MH from a set of n items takes O(n/p+log n) time. The given algorithms for insertion and deletion achieve the best possible running time for any number of processors p, with p ∈ O(log n/log log n), while the MH construction algorithm employs up to Θ(n/log n) processors optimally.
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Citations
Distributed priority queues on hypercube architectures
Sajal K. Das,F. Sarkar,M.C. Pinotti +2 more
- 27 May 1996
TL;DR: To the best of the knowledge, these algorithms provide the first implementations of b-bandwidth distributed priority queues, which are load balanced and yet guarantee optimal speed-up, in a b- bandwidth, n-item priority queue.
35
Heaps with bits
TL;DR: This paper shows how to improve the complexity of heap operations and heapsort using extra bits, and improves those of previously known algorithms.
15
Priority Queues on Parallel Machines
Gerth Stølting Brodal
- 03 Jul 1996
TL;DR: In this article, the authors presented time and work optimal priority queues for the CREW PRAM, supporting FindMin in constant time with one processor and makeQueue, Insert, Meld, Findmin, Extractmin, Delete and DecreaseKey in constant speed with O(log n) processors.
12
On the implementation of parallel shortest path algorithms on a supercomputer
Gabriele Di Stefano,Alberto Petricola,Christos D. Zaroliagis +2 more
- 04 Dec 2006
TL;DR: The authors' Hamiltonian cycle algorithm allows us to considerably improve the communication cost and thus the overall performance of the implementation of this implementation of a fast and work-efficient parallel shortest path algorithm, originally designed for an EREW PRAM.
11
•Posted Content
A Parallel Batch-Dynamic Data Structure for the Closest Pair Problem
TL;DR: This work is the first to experimentally evaluate parallel algorithms for the closest pair problem, in both the static and the dynamic settings, and finds that it is advantageous to use the dynamic algorithm for batch sizes of up to 70\% of the data set.
9
References
•Book
Introduction to Algorithms
Thomas H. Cormen,Charles E. Leiserson,Ronald L. Rivest +2 more
- 01 Jan 1990
TL;DR: The updated new edition of the classic Introduction to Algorithms is intended primarily for use in undergraduate or graduate courses in algorithms or data structures and presents a rich variety of algorithms and covers them in considerable depth while making their design and analysis accessible to all levels of readers.
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Relaxed heaps: an alternative to Fibonacci heaps with applications to parallel computation
TL;DR: The relaxed heap is a priority queue data structure that achieves the same amortized time bounds as the Fibonacci heap—a sequence of m decrease_key and n delete_min operations takes time O(m + n log n).
235
Concurrent access of priority queues
R.V. Nageshwara,Vipin Kumar +1 more
TL;DR: Experimental results on the BBN Butterfly parallel processor demonstrate that the use of concurrent-heap algorithms in parallel branch-and-bound improves its performance substantially.
113
•Proceedings Article
Simultaneous update of priority structures.
Jit Biswas,James C. Browne +1 more
- 01 Jan 1987
TL;DR: This paper demonstrates content partitioning of a k-ary tree data structure at runtime, to realize a simultaneously updatable priority queue, and the tree algorithms are generalized to banyan data structures and shown to possess attractive properties of simultaneous update and throughput.
53
Building heaps in parallel
TL;DR: O(log n) time parallel algorithms for constructing a heap of a set of n elements, chosen from a total order, using EREW PRAM and hypercube of at most [2n/log n] processors are presented.
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