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We present and evaluate a new GPU algorithm based on the Louvain method for community detection. Our algorithm is the first for this problem that parallelizes the access to individual edges. In this way we can fine tune the load balance when processing networks with nodes of highly varying degrees. This is achieved by scaling the number of threads assigned to each node according to its degree. Extensive...
K-means is the most widely used clustering algorithm due to its fairly straightforward implementations in various problems. Meanwhile, when the number of clusters increase, the number of iterations also tend to slightly increase. However there are still opportunities for improvement as some studies in the literature indicate. In this study, improved implementations of k-means algorithm with a centroid...
Along with the rapid development of parallel computing technology and the popularity of Beowulf cluster system, the scalability of parallel algorithm-machine combinations, which measures the capacity of a parallel algorithm to effectively utilize an increasing number of processors, becomes more and more important. This ratio of parallel overhead to computation is reviewed in this paper, the merit...
According to the efficiency bottleneck of algorithm DBSCAN, we present P-DBSCAN, a novel parallel version of this algorithm in distributed environment. By separating the database into several parts, the computer nodes carry out clustering independently; after that, the sub-results will be aggregated into one final result. P-DBSCAN achieves good results and much better efficiency than DBSCAN. Experiments...
FP-growth algorithm recursively generates huge amounts of conditional pattern bases and conditional FP-trees when the dataset is huge. In such a case, both the memory usage and computational cost are expensive, such that, the FP-tree can not meet the memory requirement. In this work, we propose a novel parallel FP-growth algorithm, which is designed to run on the computer cluster. To avoid memory...
Despite significant progress that has been made in developing efficient collision detection algorithms for convex polyhedrons, limited and slow progress has been reported in developing collision detection algorithm for nonconvex polyhedron. To narrow this gap we present a parallel collision detection algorithm. The algorithm consist of two stages. The first stage involves decomposing nonconvex polyhedron...
This paper analyzes the characteristics of parallel algorithm for Image and real-time processing of image which base on the cluster-computer. An improved double-sync(the bulk synchronous and the cycle of synchronization) BSP model is proposed, which provides the capability of the real-time processing. Under the clustered computer system, we adopt the leaping task allocation algorithm and the method...
This paper presents a novel model for 3D image segmentation and reconstruction. It has been designed with the aim to be implemented over a computer cluster or a multi-core platform. The required features include a nearly absolute independence between the processes participating in the segmentation task and providing amount of work as equal as possible for all the participants. As a result, it is avoid...
This paper presents alternatives and performance results obtained by analyzing parallelization on a cluster of multicore nodes. The ultimate goal is to show if both shared and distributed memory parallel processing models need to be taken into account independently, or if one affects the other and both must be considered simultaneosly. The application used as a testbed is classical in the context...
In computer graphics, global illumination algorithms take into account not only the light that comes directly from the sources, but also the light interreflections. This kind of algorithms produce very realistic images, but at a high computational cost, especially when dealing with complex environments. Parallel computation has been successfully applied to such algorithms in order to make it possible...
The knapsack problem is a typical one of NPC problems, which is easy to be described but difficult to be solved. It is very important in theory and practice to study it. Nowadays there is a variety of research in algorithm for solving it. As the parallel processing technologies develop, the research of effective parallel algorithms for this problem attracts much attention. To run those algorithms...
Based on the problem of TB level mass data lacking of parallel patterns which is distributed on Earth and accessed by Internet, we focus on the research of parallel computing architecture structure--virtual cluster based on cloud computing. Meanwhile, the parallel data mining algorithm is studied, and the effectiveness of parallel data mining algorithm based on this platform is proved.
In this paper, we describe two algorithmic techniques for the design of efficient algorithms in dual-cube. The first uses cluster structure of dual-cube, and the second uses recursive structure of the dual-cube. We propose efficient algorithms for parallel prefix computation and sorting in dual-cube based on the two techniques, respectively. For a dual-cube Dn with 22n-1 nodes and n links per node,...
An image information restoration algorithm based on Long-Range correlation (LR-IIRA) can be efficiently applied in image interpretation, restoration, and error concealment. But this algorithm requires excessive computing time, which restricts its application on large-scale problems and real time problems. We propose a parallel LR-IIRA algorithm (PLR-IIRA) to parallelize the restoration processing...
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