A Parallel Wavefront Algorithm for Efficient Biological Sequence Comparison

Alves, Carlos Eduardo Rodrigues; Cáceres, Edson Norberto; Dehne, Frank; Song, Siang Wun

doi:10.1007/3-540-44843-8_27

Cited by 28 publications

(22 citation statements)

References 12 publications

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“…In [1] we have proposed a parallel algorithm for efficient sequence alignment. In this section we show that, by using the proposed dependence transformation method, it is straightforward to generate this algorithm.…”

Section: A Parallel Algorithm For Alignment Of Sequencesmentioning

confidence: 99%

Generating Parallel Algorithms for Cluster and Grid Computing

Hayashida

Okuda

Panetta

et al. 2005

Lecture Notes in Computer Science

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Abstract. We revisit and use the dependence transformation method to generate parallel algorithms suitable for cluster and grid computing. We illustrate this method in two applications: to obtain a systolic matrix product algorithm, and to compute the alignment score of two strings. The product of two n × n matrices is viewed as multiplying two p × p matrices whose elements are n/p × n/p submatrices. For m such multiplications, using p 2 processors, the proposed parallel solution gives a linear speedup of

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Section: A Parallel Algorithm For Alignment Of Sequencesmentioning

confidence: 99%

Generating Parallel Algorithms for Cluster and Grid Computing

Hayashida

Okuda

Panetta

et al. 2005

Lecture Notes in Computer Science

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“…We have presented some parallel algorithms for finding the similarity between two strings [4,5,6]. Among these we choose the one that is very efficient in practice [6].…”

Section: Parallel String Similaritymentioning

confidence: 99%

“…Among these we choose the one that is very efficient in practice [6]. It Algorithm 1 Comparison of Genomes G and H Input: (i) the 4-letter alphabet DNA sequence of each genome G and H; (ii) the annotation with the start and end positions of the predicted genes in each DNA sequence; (iii) the genes given in terms of amino acids from a 20-letter alphabet.…”

Section: Parallel String Similaritymentioning

confidence: 99%

“…We summarize the algorithm in the section. Details can be found in [6]. This parallel algorithm uses the dynamic programming technique to compute an alignment between two strings A and C, with |A| = m and |C| = n. On a distributed memory parallel computer of p processors each with O((m + n)/p) memory, the proposed algorithm requires O(p) communication rounds and O(mn/p) local computing time.…”

Section: : Align Each Pair Of Intergenic Regionsmentioning

confidence: 99%

“…Then P 1 and P 2 can work at round 1, P 1 , P 2 and P 3 at round 2, and so on. In other words, after computing the k-th part of the sub-matrix S i (denoted S k i ), processor P i sends to processor P i+1 the elements of the right boundary (rightmost column) of S [6].…”

Section: : Align Each Pair Of Intergenic Regionsmentioning

confidence: 99%

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Comparison of genomes using high-performance parallel computing

Almeida

Cáceres

Alves

et al.

Proceedings. 15th Symposium on Computer Architecture and High Performance Computing

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Performance results of running parallel applications on the InteGrade

Cáceres

Mongelli

Loureiro

et al. 2010

Concurrency and Computation

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SUMMARYThe InteGrade middleware intends to exploit the idle time of computing resources in computer laboratories. In this work we investigate the performance of running parallel applications with communication among processors on the InteGrade grid. As costly communication on a grid can be prohibitive, we explore the so-called systolic or wavefront paradigm to design the parallel algorithms in which no global communication is used. To evaluate the InteGrade middleware we considered three parallel algorithms that solve the matrix chain product problem, the 0-1 Knapsack Problem, and the local sequence alignment problem, respectively. We show that these three applications running under the InteGrade middleware and MPI take slightly more time than the same applications running on a cluster with only LAM-MPI support. The results can be considered promising and the time difference between the two is not substantial. The overhead of the InteGrade middleware is acceptable, in view of the benefits obtained to facilitate the use of grid computing by the user. These benefits include job submission, checkpointing, security, job migration, etc.

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A Parallel Wavefront Algorithm for Efficient Biological Sequence Comparison

Cited by 28 publications

References 12 publications

Generating Parallel Algorithms for Cluster and Grid Computing

Generating Parallel Algorithms for Cluster and Grid Computing

Comparison of genomes using high-performance parallel computing

Performance results of running parallel applications on the InteGrade

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