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A framework for speeding up priorityqueue operations
, 2004
"... Abstract. We introduce a framework for reducing the number of element comparisons performed in priorityqueue operations. In particular, we give a priority queue which guarantees the worstcase cost of O(1) per minimum finding and insertion, and the worstcase cost of O(log n) with at most log n + O ..."
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Abstract. We introduce a framework for reducing the number of element comparisons performed in priorityqueue operations. In particular, we give a priority queue which guarantees the worstcase cost of O(1) per minimum finding and insertion, and the worstcase cost of O(log n) with at most log n + O(1) element comparisons per minimum deletion and deletion, improving the bound of 2log n + O(1) on the number of element comparisons known for binomial queues. Here, n denotes the number of elements stored in the data structure prior to the operation in question, and log n equals max {1,log 2 n}. We also give a priority queue that provides, in addition to the abovementioned methods, the prioritydecrease (or decreasekey) method. This priority queue achieves the worstcase cost of O(1) per minimum finding, insertion, and priority decrease; and the worstcase cost of O(log n) with at most log n + O(log log n) element comparisons per minimum deletion and deletion. CR Classification. E.1 [Data Structures]: Lists, stacks, and queues; E.2 [Data
RankPairing Heaps
"... Abstract. We introduce the rankpairing heap, a heap (priority queue) implementation that combines the asymptotic efficiency of Fibonacci heaps with much of the simplicity of pairing heaps. Unlike all other heap implementations that match the bounds of Fibonacci heaps, our structure needs only one c ..."
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Abstract. We introduce the rankpairing heap, a heap (priority queue) implementation that combines the asymptotic efficiency of Fibonacci heaps with much of the simplicity of pairing heaps. Unlike all other heap implementations that match the bounds of Fibonacci heaps, our structure needs only one cut and no other structural changes per key decrease; the trees representing the heap can evolve to have arbitrary structure. Our initial experiments indicate that rankpairing heaps perform almost as well as pairing heaps on typical input sequences and better on worstcase sequences. 1
Pairing Heaps with Costless Meld
, 2009
"... Improving the structure and analysis in [1], we give a variation of the pairing heaps that has amortized zero cost per meld (compared to an O(log log n) in [1]) and the same amortized bounds for all other operations. More precisely, the new pairing heap requires: no cost per meld, O(1) per findmin ..."
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Improving the structure and analysis in [1], we give a variation of the pairing heaps that has amortized zero cost per meld (compared to an O(log log n) in [1]) and the same amortized bounds for all other operations. More precisely, the new pairing heap requires: no cost per meld, O(1) per findmin and insert, O(log n) per deletemin, and O(log log n) per decreasekey. These bounds are the best known for any selfadjusting heap, and match the lower bound proven by Fredman for a family of such heaps. Moreover, our structure is even simpler than that in [1].
Kinetic sweep and prune for multibody continuous motion
 Computers & Graphics
, 2006
"... We propose an acceleration scheme for realtime manybody dynamic collision detection. We kinetize the sweep and prune method for manybody collision pruning, extending its application to dynamic collision detection via kinetic data structures. In doing so, we modify the method from samplerate dri ..."
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We propose an acceleration scheme for realtime manybody dynamic collision detection. We kinetize the sweep and prune method for manybody collision pruning, extending its application to dynamic collision detection via kinetic data structures. In doing so, we modify the method from samplerate driven to eventdriven, with no more events than the original method processed, also removing the perframe overhead, allowing our method to scale well in terms of framerates. Unlike many schemes for manybody collision pruning, ours performs well in both sparse and dense environments, with few or many collisions. Key words: Methodology and Techniques–Graphics data structures and data types; ThreeDimensional Graphics and RealismVirtual reality; Dynamic collision detection; Kinetic data structures
How to Find a Minimum Spanning Tree in Practice
 results and New Trends in Computer Science, volume 555 of Lecture Notes in Computer Science
, 1991
"... We address the question of theoretical vs. practical behavior of algorithms for the minimum spanning tree problem. We review the factors that influence the actual running time of an algorithm, from choice of language, machine, and compiler, through lowlevel implementation choices, to purely algor ..."
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We address the question of theoretical vs. practical behavior of algorithms for the minimum spanning tree problem. We review the factors that influence the actual running time of an algorithm, from choice of language, machine, and compiler, through lowlevel implementation choices, to purely algorithmic issues. We discuss how to design a careful experimental comparison between various alternatives. Finally, we present some results from an ongoing study in which we are using: multiple languages, compilers, and machines; all the major variants of the comparisonbased algorithms; and eight varieties of graphs with sizes of up to 130,000 vertices (in sparse graphs) or 750,000 edges (in dense graphs). 1 Introduction Finding spanning trees of minimum weight (minimum spanning trees or MSTs) is one of the best known graph problems; algorithms for this problem have a long history, for which see the article of Graham and Hell [6]. The best comparisonbased algorithm to date, due to Gabow...
Kinetic Sweep and Prune for Collision Detection
 In Proc. Workshop on Virtual Reality Interactions and Physical Simulations
, 2005
"... We propose an acceleration scheme for realtime manybody dynamic collision detection. We kinetize the sweep and prune method for manybody collision pruning, extending its application to dynamic collision detection via kinetic data structures. In doing so, we modify the method from samplerate driv ..."
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We propose an acceleration scheme for realtime manybody dynamic collision detection. We kinetize the sweep and prune method for manybody collision pruning, extending its application to dynamic collision detection via kinetic data structures. In doing so, we modify the method from samplerate driven to eventdriven, with no more events than the original method processed, also removing the perframe overhead, allowing our method to scale well in terms of framerates. Unlike many schemes for manybody collision pruning, ours performs well in both sparse and dense environments, with few or many collisions. Categories and Subject Descriptors (according to ACM CCS): I.3.6 [Computer Graphics]: Methodology and Techniques—Graphics data structures and data types; I.3.7 [Computer Graphics]: ThreeDimensional Graphics and Realism—Virtual reality
Tidy Animations of Tree Algorithms
 Usability Center, Georgia Institute of Technology, Atlanta, GA
, 1992
"... ..."
DiscreteEvent Simulation on the BulkSynchronous Parallel Model
, 1998
"... The bulksynchronous parallel (BSP) model of computing has been proposed to enable the development of portable software which achieves scalable performance across diverse parallel architectures. A number of applications of computing science have been demonstrated to be efficiently supported by the B ..."
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The bulksynchronous parallel (BSP) model of computing has been proposed to enable the development of portable software which achieves scalable performance across diverse parallel architectures. A number of applications of computing science have been demonstrated to be efficiently supported by the BSP model in practice. In this
LEDASM: External Memory Algorithms and Data Structures in Theory and Practice
, 2001
"... Data to be processed has dramatically increased during the last years. Nowadays, external memory (mostly hard disks) has to be used to store this massive data. Algorithms and data structures that work on external memory have different properties and specialties that distinguish them from algorithms ..."
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Data to be processed has dramatically increased during the last years. Nowadays, external memory (mostly hard disks) has to be used to store this massive data. Algorithms and data structures that work on external memory have different properties and specialties that distinguish them from algorithms and data structures, developed for the RAM model. In this thesis, we first explain the functionality of external memory, which is realized by disk drives. We then introduce the most important theoretical I/O models. In the main part, we present the C++ class library LEDASM. Library LEDASM is an extension of the LEDA library towards external memory computation and consists of a collection of algorithms and data structures that are designed to work efficiently in external memory. In the last two chapters, we present new external memory data structures for external memory priority queues and new external memory construction algorithms for suffix arrays. These new proposals are theoretically analyzed and experimentally tested. All proposals are implemented using the LEDASM library. Their efficiency is evaluated by performing a large number of experiments.