Search results for "A* algorithm"

SWAPHI: Smith-Waterman Protein Database Search on Xeon Phi Coprocessors

2014

The maximal sensitivity of the Smith-Waterman (SW) algorithm has enabled its wide use in biological sequence database search. Unfortunately, the high sensitivity comes at the expense of quadratic time complexity, which makes the algorithm computationally demanding for big databases. In this paper, we present SWAPHI, the first parallelized algorithm employing Xeon Phi coprocessors to accelerate SW protein database search. SWAPHI is designed based on the scale-and-vectorize approach, i.e. it boosts alignment speed by effectively utilizing both the coarse-grained parallelism from the many co-processing cores (scale) and the fine-grained parallelism from the 512-bit wide single instruction, mul…

Algorithms for Graph and Network Analysis: Graph Alignment

2019

In this article we discuss the problem of graph alignment, which has been longly referred to for the purpose of analyzing and comparing biological networks. In particular, we describe different facets of graph alignment, according to the number of input networks, the fixed output objective, the possible heterogeneity of input data. Accordingly, we will discuss pairwise and multiple alignment, global and local alignment, etc. Moreover, we provide a comprehensive overview of the algorithms and techniques proposed in the literature to solve each of the specific considered types of graph alignment. In order to make the material presented here complete and useful to guide the reader in the use o…

GSWABE: faster GPU-accelerated sequence alignment with optimal alignment retrieval for short DNA sequences

2014

In this paper, we present GSWABE, a graphics processing unit GPU-accelerated pairwise sequence alignment algorithm for a collection of short DNA sequences. This algorithm supports all-to-all pairwise global, semi-global and local alignment, and retrieves optimal alignments on Compute Unified Device Architecture CUDA-enabled GPUs. All of the three alignment types are based on dynamic programming and share almost the same computational pattern. Thus, we have investigated a general tile-based approach to facilitating fast alignment by deeply exploring the powerful compute capability of CUDA-enabled GPUs. The performance of GSWABE has been evaluated on a Kepler-based Tesla K40 GPU using a varie…

Accelerating large-scale biological database search on Xeon Phi-based neo-heterogeneous architectures

2015

In this paper we present new parallelization techniques for searching large-scale biological sequence databases with the Smith-Waterman algorithm on Xeon Phi-based neoheterogenous architectures. In order to make full use of the compute power of both the multi-core CPU and the many-core Xeon Phi hardware, we use a collaborative computing scheme as well as hybrid parallelism. At the CPU side, we employ SSE intrinsics and multi-threading to implement SIMD parallelism. At the Xeon Phi side, we use Knights Corner vector instructions to gain more data parallelism. We have presented two dynamic task distribution schemes (thread level and device level) in order to achieve better load balancing. Fur…

Splitting the data cache: a survey

2000

Recent cache-memory research has focused on approaches that split the first-level data cache into two independent subcaches. The authors introduce a methodology for helping cache designers devise splitting schemes and survey a representative set of the published cache schemes.

Procrastination out of Habit? The Role of Impulsive Versus Reflective Media Selection in Procrastinatory Media Use

2018

The pervasive access to media options seriously challenges users’ self-regulatory abilities. One example of deficient self-regulation in the context of media use is procrastination—impulsively ‘giving in’ to available media options despite goal conflicts with more important tasks. This study investigaes procrastinatory media use across 3 types of media (TV, computer, smartphone) from a dual-systems perspective, taking both person-level and situation-level predictors into account. Results from a 14-day long diary study (N = 347) suggest that procrastinatory media use is driven by automatic media selection, which is facilitated by strong media habits (person level) and low motivation for beha…

Training and selection of sport psychologists: An international review

2003

Does Navigation Always Predict Performance? Effects of Navigation on Digital Reading are Moderated by Comprehension Skills

2016

<p align="left">This study investigated interactive effects of navigation and offline comprehension skill on digital reading performance. As indicators of navigation relevant page selection and irrelevant page selection were considered. In 533 Spanish high school students aged 11-17 positive effects of offline comprehension skill and relevant page selection on digital reading performance were found, while irrelevant page selection had a negative effect. In addition, an interaction between relevant page selection and offline comprehension skill was found. While the effect of relevant page selection was strong in good offline comprehenders, it was significantly reduced in weak offline c…

Identifying the k Best Targets for an Advertisement Campaign via Online Social Networks

2020

We propose a novel approach for the recommendation of possible customers (users) to advertisers (e.g., brands) based on two main aspects: (i) the comparison between On-line Social Network profiles, and (ii) neighborhood analysis on the On-line Social Network. Profile matching between users and brands is considered based on bag-of-words representation of textual contents coming from the social media, and measures such as the Term Frequency-Inverse Document Frequency are used in order to characterize the importance of words in the comparison. The approach has been implemented relying on Big Data Technologies, allowing this way the efficient analysis of very large Online Social Networks. Resul…

Clique Percolation Method: Memory Efficient Almost Exact Communities

2022

Automatic detection of relevant groups of nodes in large real-world graphs, i.e. community detection, has applications in many fields and has received a lot of attention in the last twenty years. The most popular method designed to find overlapping communities (where a node can belong to several communities) is perhaps the clique percolation method (CPM). This method formalizes the notion of community as a maximal union of $k$-cliques that can be reached from each other through a series of adjacent $k$-cliques, where two cliques are adjacent if and only if they overlap on $k-1$ nodes. Despite much effort CPM has not been scalable to large graphs for medium values of $k$. Recent work has sho…