14651264
Computing Maximum Subsequence in Parallel
The maximum subsequence problem finds the contiguous subsequence of n real numbers with the highest sum. This is an important problem that arises in several contexts in Computational Biology in the analysis of DNA or protein sequences. The maximum subsequence problem of n given scores can be solved sequentially in O(n) time. In this paper we present an efficient BSP/CGM parallel algorithm that requires a constant number of communication rounds. In the proposed algorithm, the input is partitioned equally among the processors and the sequence stored on each processor is reduced to only five numbers. This reduction is crucial as it allows all the resulting values to be concentrated on a single processor which runs an adaptation of the sequential algorithm to obtain the result. The amount of data transmitted is 5p where p is the number of processors, thus independent of the input size n. The good performance of the parallel algorithm is confirmed by experimental results run on a 64-node Beowulf parallel computer, giving almost linear speedup. Topic of interest: Algorithms and Software Tools for Computational Molecular Biology
17543628
Efficient Implementation of the BSP/CGM Parallel Vertex Cover FPT Algorithm
In many applications NP-complete problems need to be solved exactly. One promising method to treat some intractable problems is by considering the so-called Parameterized Complexity that divides the problem input into a main part and a parameter. The main part of the input contributes polynomially on the total complexity of the problem, while the parameter is responsible for the combinatorial explosion. We consider the parallel FPT algorithm of Cheetham et al. to solve the k-Vertex Cover problem, using the CGM model. Our contribution is to present a refined and improved implementation. In our parallel experiments, we obtained better results and obtained smaller cover sizes for some input data. The key idea for these results was the choice of good data structures and use of the backtracking technique. We used 5 graphs that represent conflict graphs of amino acids, the same graphs used also by Cheetham et al. in their experiments. For two of these graphs, the times we obtained were approximately 115 times better, for one of them 16 times better, and, for the remaining graphs, the obtained times were slightly better. We must also emphasize that we used a computational environment that is inferior than that used in the experiments of Cheetham et al.. Furthermore, for three graphs, we obtained smaller sizes for the cover.
15372293
Broadcasting in Bus Interconnection Networks
In this paper we study parallel architectures where the communication means are constituted solely by buses. These promising architectures can use the power of bus technologies, providing a viable way to interconnect much more processors in a simple and efficient manner. We study the hyperpath, hypergrid, hyperring, and hypertorus architectures, which are the bus-based versions of the well used point-to-point interconnection networks. We give optimal algorithms for broadcasting a message from one processor to all the others in such architectures, using a tool called simplification.
13919002
Efficient embeddings into the hypercube using matrix transformations
The embedding of one interconnection network into another is a very important issue in the design and analysis of parallel algorithms. Through such embedding the algorithms originally developed for one architecture can be directly mapped to another architecture. This paper describes novel methods, based on matrix transformations, for e~ciently embedding different networks into the hypercube (binary n-cube). First, we use this method to embed r-ary m-cubes into a binary n-cube of the same size with dilation 1. While our method has the same dilation as traditional methods using rejlected Gray code, it has the additional property of making the layout of the binary n-cube more suitable for divide-and-conquer algorithms. Second, we use our matrix transformation method to optimally embed hierarchical interconnection networks into the binary n-cube which we would not achieve using rejlected Gray code embedding. Thus, this embedding method has signi$cant practical importance in enhancing the capabilities of the hypercube..
17783880
TCUAP: A Novel Approach of Text Clustering Using Asymmetric Proximity
Text documents have sparse data spaces and current existing methods of text clustering use symmetry proximity to measure the correlation of documents. In this paper, we propose a novel approach to strengthen the discriminative feature of document objects, which uses asymmetric proximity for text clustering. We present a measure of asymmetric proximity between documents and between clusters. TCUAP is an agglomerative hierarchical clustering algorithm and carries on the clustering analysis by strong components of sparse matrix. The experimental evaluation on textual data sets demonstrates the validity and efficiency of our approach. The result shows that the measure of asymmetric proximity possesses higher accuracy than that of symmetry proximity.
2193712
Similarity Joins of Text with Incomplete Information Formats
Similarity join over text is important in text retrieval and query. Due to the incomplete formats of information representation, such as abbreviation and short word, similarity joins should address an asymmetric feature that these incomplete formats may contain only partial information of their original representation. Current approaches, including cosine similarity with q-grams, can hardly deal with the asymmetric feature of similarity between words and their incomplete formats. In order to find this type of incomplete format information with asymmetric features, we develop a new similarity join algorithm, namely IJoin. A novel matching scheme is proposed to identify the overlap between two entities with incomplete formats. Other than q-grams, we reconnect the sequence of words in a string to reserve the abbreviated information. Based on the asymmetric features of similar entities with incomplete formats, we adopt a new similarity function. Furthermore, an efficient algorithm is implemented by using the join operation in SQL, which reduces pairs of tuples in similarity comparison. The experimental evaluation demonstrates the effectiveness and the efficiency of our approach.