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A Randomized LinearTime Algorithm to Find Minimum Spanning Trees
, 1994
"... We present a randomized lineartime algorithm to find a minimum spanning tree in a connected graph with edge weights. The algorithm uses random sampling in combination with a recently discovered lineartime algorithm for verifying a minimum spanning tree. Our computational model is a unitcost ra ..."
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Cited by 115 (7 self)
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We present a randomized lineartime algorithm to find a minimum spanning tree in a connected graph with edge weights. The algorithm uses random sampling in combination with a recently discovered lineartime algorithm for verifying a minimum spanning tree. Our computational model is a unitcost randomaccess machine with the restriction that the only operations allowed on edge weights are binary comparisons.
A linearwork parallel algorithm for finding . . .
, 1994
"... We give the first linearwork parallel algorithm for finding a minimum spanning tree. It is a randomized algorithm, and requires O(2log \Lambda n log n) expected time. It is a modification of the sequential lineartime algorithm of Klein and Tarjan. ..."
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Cited by 14 (1 self)
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We give the first linearwork parallel algorithm for finding a minimum spanning tree. It is a randomized algorithm, and requires O(2log \Lambda n log n) expected time. It is a modification of the sequential lineartime algorithm of Klein and Tarjan.
Motorcycle Graphs and Straight Skeletons
, 2002
"... We present a new algorithm to compute a motorcycle graph. It runs in O(n p n log n) time when n is the size of the input. We give a new characterization of the straight skeleton of a polygon possibly with holes. ..."
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Cited by 13 (1 self)
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We present a new algorithm to compute a motorcycle graph. It runs in O(n p n log n) time when n is the size of the input. We give a new characterization of the straight skeleton of a polygon possibly with holes.
MST Construction in O(log log n) Communication Rounds
 In Proceedings of the 15 th ACM symposium on Parallel Algorithms and Architectures (SPAA
, 2003
"... We consider a simple model for overlay networks, where all n processes are connected to all other processes, and each message contains at most O(log n) bits. For this model, we present a distributed algorithm that constructs a minimumweight spanning tree in O(log log n) communication rounds, where i ..."
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Cited by 9 (1 self)
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We consider a simple model for overlay networks, where all n processes are connected to all other processes, and each message contains at most O(log n) bits. For this model, we present a distributed algorithm that constructs a minimumweight spanning tree in O(log log n) communication rounds, where in each round any process can send a message to each other process. This result is the first to break the Ω(log n) parallel time complexity barrier with small message sizes. 1.
Tetra: Evaluation of Serial Program Performance on FineGrain Parallel Processors
 University of Wisconsin
, 1993
"... Tetra is a tool for evaluating serial program performance under the resource and control constraints of finegrain parallel processors. Tetra's primary advantage to the architect is its ability to quickly generate performance metrics for yet to be designed architectures. All the user needs to specif ..."
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Cited by 6 (0 self)
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Tetra is a tool for evaluating serial program performance under the resource and control constraints of finegrain parallel processors. Tetra's primary advantage to the architect is its ability to quickly generate performance metrics for yet to be designed architectures. All the user needs to specify is the capabilities of the architecture (e.g., number of functional units, issue model, etc.), rather than its implementation. Tetra first extracts a canonical form of the program from a serial instruction trace. It then applies control and resource constraint scheduling to produce an execution graph. The control and resource constraint scheduling is directed by a processor model specification supplied to the program. Once scheduled, Tetra provides a number of ways to analyze the program's performance under the specified processor model. These include parallelism profiles, storage demand profiles, data sharing distributions, data lifetime analysis, and control distance (branch, loop, and ...
Improved Symmetric Lists
, 2004
"... We introduce a new data structure called symlist based on an idea of Tarjan [17]. A symlist is a doubly linked list without any directional information encoded into its cells. In a symlist the two pointers in each cell have no fixed meaning like previous or next in standard lists. ..."
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Cited by 2 (2 self)
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We introduce a new data structure called symlist based on an idea of Tarjan [17]. A symlist is a doubly linked list without any directional information encoded into its cells. In a symlist the two pointers in each cell have no fixed meaning like previous or next in standard lists.