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28
Parallel Algorithms with Optimal Speedup for Bounded Treewidth
 Proceedings 22nd International Colloquium on Automata, Languages and Programming
, 1995
"... We describe the first parallel algorithm with optimal speedup for constructing minimumwidth tree decompositions of graphs of bounded treewidth. On nvertex input graphs, the algorithm works in O((logn)^2) time using O(n) operations on the EREW PRAM. We also give faster parallel algorithms with opti ..."
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Cited by 33 (10 self)
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We describe the first parallel algorithm with optimal speedup for constructing minimumwidth tree decompositions of graphs of bounded treewidth. On nvertex input graphs, the algorithm works in O((logn)^2) time using O(n) operations on the EREW PRAM. We also give faster parallel algorithms with optimal speedup for the problem of deciding whether the treewidth of an input graph is bounded by a given constant and for a variety of problems on graphs of bounded treewidth, including all decision problems expressible in monadic secondorder logic. On nvertex input graphs, the algorithms use O(n) operations together with O(log n log n) time on the EREW PRAM, or O(log n) time on the CRCW PRAM.
Shared Memory Simulations with TripleLogarithmic Delay (Extended Abstract)
, 1995
"... ) Artur Czumaj 1 , Friedhelm Meyer auf der Heide 2 , and Volker Stemann 1 1 Heinz Nixdorf Institute, University of Paderborn, D33095 Paderborn, Germany 2 Heinz Nixdorf Institute and Department of Computer Science, University of Paderborn, D33095 Paderborn, Germany Abstract. We conside ..."
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Cited by 21 (4 self)
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) Artur Czumaj 1 , Friedhelm Meyer auf der Heide 2 , and Volker Stemann 1 1 Heinz Nixdorf Institute, University of Paderborn, D33095 Paderborn, Germany 2 Heinz Nixdorf Institute and Department of Computer Science, University of Paderborn, D33095 Paderborn, Germany Abstract. We consider the problem of simulating a PRAM on a distributed memory machine (DMM). Our main result is a randomized algorithm that simulates each step of an nprocessor CRCW PRAM on an nprocessor DMM with O(log log log n log n) delay, with high probability. This is an exponential improvement on all previously known simulations. It can be extended to a simulation of an (n log log log n log n) processor EREW PRAM on an nprocessor DMM with optimal delay O(log log log n log n), with high probability. Finally a lower bound of \Omega (log log log n=log log log log n) expected time is proved for a large class of randomized simulations that includes all known simulations. 1 Introduction Para...
Optimally Fast Parallel Algorithms for Preprocessing and Pattern Matching in One and Two Dimensions
, 1993
"... All algorithms below are optimal alphabetindependent parallel CRCW PRAM algorithms. In one dimension: Given a pattern string of length m for the stringmatching problem, we design an algorithm that computes a deterministic sample of a sufficiently long substring in constant time. This problem use ..."
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Cited by 19 (10 self)
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All algorithms below are optimal alphabetindependent parallel CRCW PRAM algorithms. In one dimension: Given a pattern string of length m for the stringmatching problem, we design an algorithm that computes a deterministic sample of a sufficiently long substring in constant time. This problem used to be a bottleneck in the pattern preprocessing for one and twodimensional pattern matching. The best previous time bound was O(log 2 m= log log m). We use this algorithm to obtain the following results. 1. Improving the preprocessing of the constanttime text search algorithm [12] from O(log 2 m= log log m) to O(log log m), which is now best possible. 2. A constanttime deterministic stringmatching algorithm in the case that the text length n satisfies n = \Omega\Gamma m 1+ffl ) for a constant ffl ? 0. 3. A simple probabilistic stringmatching algorithm that has constant time with high probability for random input. 4. A constant expected time LasVegas algorithm for computing t...
Optimal Deterministic Approximate Parallel Prefix Sums and Their Applications
 In Proc. Israel Symp. on Theory and Computing Systems (ISTCS'95
, 1995
"... We show that extremely accurate approximation to the prefix sums of a sequence of n integers can be computed deterministically in O(log log n) time using O(n= log log n) processors in the Common CRCW PRAM model. This complements randomized approximation methods obtained recently by Goodrich, Matias ..."
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Cited by 14 (0 self)
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We show that extremely accurate approximation to the prefix sums of a sequence of n integers can be computed deterministically in O(log log n) time using O(n= log log n) processors in the Common CRCW PRAM model. This complements randomized approximation methods obtained recently by Goodrich, Matias and Vishkin and improves previous deterministic results obtained by Hagerup and Raman. Furthermore, our results completely match a lower bound obtained recently by Chaudhuri. Our results have many applications. Using them we improve upon the best known time bounds for deterministic approximate selection and for deterministic padded sorting. 1 Introduction The computation of prefix sums is one of the most basic tools in the design of fast parallel algorithms (see Blelloch [9] and J'aJ'a [33]). Prefixsums can be computed in O(logn) time and linear work in the EREW PRAM model (Ladner and Fischer [34]) and in O(log n= log log n) and linear work in the Common CRCW PRAM model (Cole and Vishkin...
Optimal Logarithmic Time Randomized Suffix Tree Construction
 In Proc 23rd ICALP
, 1996
"... The su#x tree of a string, the fundamental data structure in the area of combinatorial pattern matching, has many elegant applications. In this paper, we present a novel, simple sequential algorithm for the construction of su#x trees. We are also able to parallelize our algorithm so that we settl ..."
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Cited by 14 (3 self)
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The su#x tree of a string, the fundamental data structure in the area of combinatorial pattern matching, has many elegant applications. In this paper, we present a novel, simple sequential algorithm for the construction of su#x trees. We are also able to parallelize our algorithm so that we settle the main open problem in the construction of su#x trees: we give a Las Vegas CRCW PRAM algorithm that constructs the su#x tree of a binary string of length n in O(log n) time and O(n) work with high probability. In contrast, the previously known workoptimal algorithms, while deterministic, take# (log n) time.
On the Power of Arrays with Reconfigurable Optical Buses
, 1996
"... This paper examines some computational aspects of different arrays enhanced with optical pipelined buses. The array processors with optical pipelined buses (APPB) are shown to be extremely flexible, as demonstrated by their ability to efficiently simulate different variants of PRAMs and bounded degr ..."
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Cited by 13 (2 self)
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This paper examines some computational aspects of different arrays enhanced with optical pipelined buses. The array processors with optical pipelined buses (APPB) are shown to be extremely flexible, as demonstrated by their ability to efficiently simulate different variants of PRAMs and bounded degree networks. A model of computation is introduced, the array with reconfigurable optical buses (AROB), which combines some of the advantages and characteristics of the classical reconfigurable networks (RN) and the APPB. A number of applications of the APPB and AROB are presented, and their power is investigated. It is shown that beside AROB's capability of simulating classical reconfigurable networks, the enhanced communication mechanisms allow for an important system reduction when compared with the classical RNs. Keywords: optical interconnections, pipelined optical buses, reconfigurable networks, bounded degree networks, PRAM models. 1 Introduction Interprocessor communication networks...
Structural Parallel Algorithmics
, 1991
"... The first half of the paper is a general introduction which emphasizes the central role that the PRAM model of parallel computation plays in algorithmic studies for parallel computers. Some of the collective knowledgebase on nonnumerical parallel algorithms can be characterized in a structural way ..."
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Cited by 11 (4 self)
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The first half of the paper is a general introduction which emphasizes the central role that the PRAM model of parallel computation plays in algorithmic studies for parallel computers. Some of the collective knowledgebase on nonnumerical parallel algorithms can be characterized in a structural way. Each structure relates a few problems and technique to one another from the basic to the more involved. The second half of the paper provides a bird'seye view of such structures for: (1) list, tree and graph parallel algorithms; (2) very fast deterministic parallel algorithms; and (3) very fast randomized parallel algorithms. 1 Introduction Parallelism is a concern that is missing from "traditional" algorithmic design. Unfortunately, it turns out that most efficient serial algorithms become rather inefficient parallel algorithms. The experience is that the design of parallel algorithms requires new paradigms and techniques, offering an exciting intellectual challenge. We note that it had...
Contention Resolution in Hashing Based Shared Memory Simulations
"... In this paper we study the problem of simulating shared memory on the Distributed Memory Machine (DMM). Our approach uses multiple copies of shared memory cells, distributed among the memory modules of the DMM via universal hashing. Thus the main problem is to design strategies that resolve cont ..."
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Cited by 9 (3 self)
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In this paper we study the problem of simulating shared memory on the Distributed Memory Machine (DMM). Our approach uses multiple copies of shared memory cells, distributed among the memory modules of the DMM via universal hashing. Thus the main problem is to design strategies that resolve contention at the memory modules. Developing ideas from random graphs and very fast randomized algorithms, we present new simulation techniques that enable us to improve the previously best results exponentially. Particularly, we show that an nprocessor CRCW PRAM can be simulated by an nprocessor DMM with delay O(log log log n log n), with high probability. Next we show a general technique that can be used to turn these simulations to timeprocessor optimal ones, in the case of EREW PRAMs to be simulated. We obtain a timeprocessor optimal simulation of an (n log log log n log n)processor EREW PRAM on an nprocessor DMM with O(log log log n log n) delay. When a CRCW PRAM with (n...
Efficient String Algorithmics
, 1992
"... Problems involving strings arise in many areas of computer science and have numerous practical applications. We consider several problems from a theoretical perspective and provide efficient algorithms and lower bounds for these problems in sequential and parallel models of computation. In the sequ ..."
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Cited by 8 (6 self)
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Problems involving strings arise in many areas of computer science and have numerous practical applications. We consider several problems from a theoretical perspective and provide efficient algorithms and lower bounds for these problems in sequential and parallel models of computation. In the sequential setting, we present new algorithms for the string matching problem improving the previous bounds on the number of comparisons performed by such algorithms. In parallel computation, we present tight algorithms and lower bounds for the string matching problem, for finding the periods of a string, for detecting squares and for finding initial palindromes.
Lower Bounds for Randomized Exclusive Write PRAMs
 in Proc. 7th ACM Symp. on Parallel Algorithms and Architectures, (ACM
, 1995
"... In this paper we study the question: How useful is randomization in speeding up Exclusive Write PRAM computations? Our results give further evidence that randomization is of limited use in these types of computations. First we examine a compaction problem on both the CREW and EREW PRAM models, and w ..."
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Cited by 7 (0 self)
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In this paper we study the question: How useful is randomization in speeding up Exclusive Write PRAM computations? Our results give further evidence that randomization is of limited use in these types of computations. First we examine a compaction problem on both the CREW and EREW PRAM models, and we present randomized lower bounds which match the best deterministic lower bounds known. (For the CREW PRAM model, the lower bound is asymptotically optimal.) These are the first nontrivial randomized lower bounds known for the compaction problem on these models. We show that our lower bounds also apply to the problem of approximate compaction. Next we examine the problem of computing boolean functions on the CREW PRAM model, and we present a randomized lower bound which improves on the previous best randomized lower bound for many boolean functions, including the OR function. (The previous lower bounds for these functions were asymptotically optimal, but we improve the constant multiplicat...