In the last few years, molecular biology has produced a large amount of data, mainly in the form of sequences, that is, strings over am alphabet of four (DNA/RNA) or twenty symbols (proteins). For computational biolog...
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ISBN:
(纸本)3540425225
In the last few years, molecular biology has produced a large amount of data, mainly in the form of sequences, that is, strings over am alphabet of four (DNA/RNA) or twenty symbols (proteins). For computational biologists the main challenge now is to provide efficient tools for the analysis and the comparison of the sequences. In this paper, we introduce and briefly discuss some open problems, and present a parallel algorithm that finds repeated substrings in a DNA sequence or common substrings in a set of sequences. The occurrences of the substrings can be approximate, that is, can differ up to a maximum number of mismatches that depends on the length of the substring itself. The output of the algorithm is sorted according to different statistical measures of significance. The algorithm has been successfully implemented on a cluster of workstations.
The index-permutation graph (IPG) model is a natural extension of the Cayley graph model, and super-IPGs form an efficient class of IPGs that contain a wide variety of networks as subclasses. In this paper, we derive ...
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ISBN:
(纸本)0769512577;0769512585
The index-permutation graph (IPG) model is a natural extension of the Cayley graph model, and super-IPGs form an efficient class of IPGs that contain a wide variety of networks as subclasses. In this paper, we derive a number of efficient algorithms and embeddings for super-IPGs, proving their versatility. We show that a multitude of important networks can also be emulated in super-IPGs with optimal slowdown. Also, the intercluster diameter, average intercluster distance, and bisection bandwidth of suitably constructed super-IPGs are optimal within small constant factors. Finally, we show that when parallel computers, built as multiple chip-multiprocessors (MCMP), are based on super-IPGs, they can significantly outperform those based on hypercubes, k-ary n-cubes, and other networks in carrying out communication-intensive tasks.
Summary form only given. Pricing of derivatives is one of the central problems in computational finance. Since the theory of derivative pricing is highly mathematical, numerical techniques such as binomial lattice, fi...
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Summary form only given. Pricing of derivatives is one of the central problems in computational finance. Since the theory of derivative pricing is highly mathematical, numerical techniques such as binomial lattice, finite-differencing and fast Fourier transform (FFT) among others have been used for derivative or option pricing. Based on a recent work on FFT for VLSI circuits, we develop a parallel algorithm in the current work, which improves data locality and hence reduce communication overheads. Our main aim is to study the performance of this algorithm. Compared to the traditional butterfly network, the current algorithm with data swap network performs better by more than 15% for large data sizes.
Many parallel algorithms for graph problems start with finding a spanning tree and rooting the tree to define some structural relationship on the vertices which can be used by following problem specific computations. ...
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Many parallel algorithms for graph problems start with finding a spanning tree and rooting the tree to define some structural relationship on the vertices which can be used by following problem specific computations. The generic procedure is to find an unrooted spanning tree and then root the spanning tree using the Euler tour technique. With a randomized work-time optimal unrooted spanning tree algorithm and work-time optimal list ranking, finding rooted spanning trees can be done work-time optimally on EREW PRAM w.h.p. Yet the Euler tour technique assumes as "given" a circular adjacency list, it is not without implications though to construct the circular adjacency list for the spanning tree found on the fly by a spanning tree algorithm. In fact our experiments show that this "hidden" step of constructing a circular adjacency list could take as much time as both spanning tree and list ranking combined. We present new efficient algorithms that find rooted spanning trees without using the Euler tour technique and incur little or no overhead over the underlying spanning tree algorithms. We also present two new approaches that construct Euler tours efficiently when the circular adjacency list is not given. One is a deterministic PRAM algorithm and the other is a randomized algorithm in the symmetric multiprocessor (SMP) model. The randomized algorithm takes a novel approach for the problems of constructing the Euler tour and rooting a tree. It computes a rooted spanning tree first, then constructs an Euler tour directly for the tree using depth-first traversal. The tour constructed is cache-friendly with adjacent edges in the tour stored in consecutive locations of an array so that prefix-sum (scan) can be used for tree computations instead of the more expensive list-ranking.
In this paper, we present parallel algorithms for Web log mining and the performance prediction model. The algorithm, based on WAP-tree, scans dataset only twice and avoids candidate generation process. We parallelize...
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In this paper, we present parallel algorithms for Web log mining and the performance prediction model. The algorithm, based on WAP-tree, scans dataset only twice and avoids candidate generation process. We parallelized mining part of WAP tree. To balance the workload among processors, we developed a task scheduling strategy. A performance model of parallel Web mining algorithm is also developed to predict the performance of parallel implementation. This model shows that we can get linear speedup for a small number of processors, and a slow down of speedup as the number of processors increases. Using the performance model, we can also estimate the maximum speed up. We implemented the algorithm on a Pittsburg Super Computer Center Lemieux using up to 48 processors. Our benchmark results showed that the performance model correctly predicts the performance of the parallel implementation. We have achieved a good speedup as the size of the dataset is increased.
Systems able to cope with very large text collections are making intensive use of distributed memory parallel computing platforms such as clusters of PCs. This is particularly evident in Web search engines which must ...
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Systems able to cope with very large text collections are making intensive use of distributed memory parallel computing platforms such as clusters of PCs. This is particularly evident in Web search engines which must resort to parallelism in order to deal efficiently with both high rates of queries per unit time and high space requirements in the form of large numbers of small documents stored in secondary memory. Those documents can be stored in compressed format to reduce memory space and communication time. This paper proposes a parallel algorithm for compressing text in such a distributed memory environment. We show efficient performance against the usual-practice alternative of compressing the whole text on a single machine.
This paper presents a parallel algorithm for histogram image template matching using an SIMD array processor with a hypercube interconnection network. For an N/spl times/N image and M/spl times/M template window, the ...
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This paper presents a parallel algorithm for histogram image template matching using an SIMD array processor with a hypercube interconnection network. For an N/spl times/N image and M/spl times/M template window, the time complexity is shown to be reduced to O(M+log/sup 2/M+logN) as compared to O(N/sup 2/M/sup 2/) for the sequential algorithm, for the N/sup 2/ processing element (PE) multiprocessor systems. Each PE requires only a small local memory. The algorithm is shown to be cost optimal with total cost of computation is O(N/sup 2/M+N/sup 2/log/sup 2/M+N/sup 2/logN).
A heuristic algorithm for the DNA sequence assembly problem is presented. Its sequential implementation is described as well as its parallelization method. A computational experiment shows how the parallel algorithm s...
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A heuristic algorithm for the DNA sequence assembly problem is presented. Its sequential implementation is described as well as its parallelization method. A computational experiment shows how the parallel algorithm speed depends on a number of processes. Tests on real data from experiments with the SARS coronavirus are also discussed, and the outcome of our algorithm appears to be biologically correct.
In the paper the new approach to design parallel algorithms for the modelling of the multi-scale non-stationary processes is proposed. Our technique is based on the explicit multi-level difference schemes with the loc...
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Floorplanning is a critical phase in the physical design of VLSI circuits and has been acknowledged as a computation-intensive process. As a result, several research efforts have been undertaken to parallelize the alg...
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ISBN:
(纸本)0780386477
Floorplanning is a critical phase in the physical design of VLSI circuits and has been acknowledged as a computation-intensive process. As a result, several research efforts have been undertaken to parallelize the algorithm. While previous work has been focused on slicing the floorplan, we present a parallel algorithm for a non-slicing floorplan using corner block list (CBL) topological representation. A parallel interconnection cost calculation algorithm with load balancing strategy is initiated in order to speed up the especially time consuming wire length calculation in floorplanning. A multiple Markov chains strategy is also embedded in our algorithm. The experimental results obtained from the tests on MCNC benchmarks indicate considerable speedup and preserved floorplanning quality.
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