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...airwise Distance Calculation Calculating similarity or dissimilarity between each element of a data set with each element in another data set is a common problem and is generally known as an All-pairs=-=[22]-=- problem. The application we have selected calculates the Smith Waterman Gotoh(SW-G)[23] distance (say ...

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...the authors compare the performance with Hadoop for tera-sort application. Sphere stores intermediate data on files, and hence is susceptible to higher overheads for iterative applications. All-Paris =-=[26]-=- is an abstraction that can be used to solve a common problem of comparing all the elements in a data set with all the elements in another data set by applying a given function. This problem can be im...

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...milar documents, set-similarity joins [6] for efficient string similarity computation in databases, pairwise distance computation [16] for clustering complex objects, and all-pairs matrix computation =-=[17]-=- for scientific computing. All approaches follow a similar idea like ER using blocking: One or more signatures (e.g., tokens or terms) are generated per object (e.g., document) to avoid the computatio...

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...roducing the Pareto-front in order to compare policy performances [36]. An improved version [37] uses the count that one particular policy dominates others as ameasure of the goodness of the policy. Ourmethod extends the Pareto-frontmethod by employing a new noise level estimation method as introduced in Section 4.2. Recently, Duan et al. [1] suggested a low complexity gametheoretic optimization method. Dogan and Özgüner [29] developed a matching and scheduling algorithm for both the execution time and the failure probability that can trade off them to get an optimal selection. Moretti et al. [38] suggested all of the pairs to improve usability, performance, and efficiency of a campus grid. Wieczorek et al. [6] analyzed five facetswhichmayhave amajor impact on the selection of an appropriate scheduling strategy, and proposed taxonomies for multi-objective workflow scheduling. Prodan and Wieczorek [30] proposed a novel dynamic constraint F. Zhang et al. / Future Generation Computer Systems 37 (2014) 309–320 311algorithm that outperforms many existing methods, such as LOSS and BDLS to optimize bi-criteria problems. Calheiros et al. [39] used a cloud coordinator to scale applications in t...

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...cution in distributed environments, e.g., MapReduce [29] and MasterSlave [28]. We are extending this generic higher-order actor set to support more data-parallel execution patterns, such as All-Pairs =-=[18]-=-, and Match and CoGroup in PACT [5]. These higherorder actors will reused to build domain-specific bioActors. • bioKepler: The bioKepler module contains a specialized set of actors, namely bioActors, ...

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...t the extreme case where the locality issinfinitely large, there would be only one file on one computesnode, eventually all the tasks need to be run on that node.s2) All-Pairs in BiometricssAll-Pairs =-=[31]-=- is a common benchmark for data-intensivesapplications that describes the behavior of a new function onssets A and sets B. For example, in Biometrics, it is verysimportant to find out the covariance o...

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...on for the many subsets of the input records. The workflow of the three distributed grouped aggregation approaches is shown in Figure 2. 3.1.Pleasingly Parallel Application The Alu clustering problem =-=[11]-=- [12] is one of the most challenging problems when sequencing clustering because Alus represent the largest repeat families in the human genome. About one million copies of the Alu sequence exist in t...

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.... Pairwise sequence alignment (PSA) does all-pair sequence alignment over a given sequence dataset, which is usually in FASTA format, where the result is generated as an all-pair dissimilarity matrix =-=[16]-=-. There are many pairwise sequence alignment algorithms, such as SmithWaterman-GOTOH (SWG) [17] and Needleman-Wunsch [18]. In this particular pipeline, we use SWG algorithm for the each pair’s sequenc...