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Yifei Li
Measuring the similarity between two streamlines is fundamental to many important flow data analysis and visualization tasks such as feature detection, pattern querying and streamline clustering. This dissertation presents a novel streamline similarity measure inspired by the bag-of-features concept from computer vision. Different from other streamline similarity measures, the proposed one considers both the distribution […]
Nadesh Ramanathan, John Wickerson, Felix Winterstein, George A. Constantinides
We provide a case study of work-stealing, a popular method for run-time load balancing, on FPGAs. Following the Cederman-Tsigas implementation for GPUs, we synchronize workitems not with locks, mutexes or critical sections, but instead with the atomic operations provided by Altera’s OpenCL SDK. We evaluate work-stealing for FPGAs by synthesizing a K-means clustering algorithm on […]
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Mishal Almazrooie, Mogana Vadiveloo, Rosni Abdullah
In this paper, a fast and practical GPU-based implementation of Fuzzy C-Means (FCM) clustering algorithm for image segmentation is proposed. First, an extensive analysis is conducted to study the dependency among the image pixels in the algorithm for parallelization. The proposed GPU-based FCM has been tested on digital brain simulated dataset to segment white matter(WM), […]
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Min Gyung Song, Dongweon Yoon
Today, there is no one who disagrees on how important data is in every industry especially in enterprise market. More recently, the key point that decides the survival of a business is the management of their big data, which is defined by the 3V’s: Volume, Velocity, and Variety [1]. While the rate of data generation […]
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James Lemon, Sinan Kockara, Tansel Halic, Mutlu Mete
BACKGROUND: Dermoscopy is a highly effective and noninvasive imaging technique used in diagnosis of melanoma and other pigmented skin lesions. Many aspects of the lesion under consideration are defined in relation to the lesion border. This makes border detection one of the most important steps in dermoscopic image analysis. In current practice, dermatologists often delineate […]
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Carl Yuheng Ren, Victor Adrian Prisacariu, Ian D Reid
We introduce a parallel GPU implementation of the Simple Linear Iterative Clustering (SLIC) superpixel segmentation. Using a single graphic card, our implementation achieves speedups of up to 83x from the standard sequential implementation. Our implementation is fully compatible with the standard sequential implementation and the software is now available online and is open source.
Mario Levorato, Lucia Drummond, Yuri Frota, Rosa Figueiredo
The solution of the Correlation Clustering (CC) problem can be used as a criterion to measure the amount of balance in signed social networks, where positive (friendly) and negative (antagonistic) interactions take place. Metaheuristics have been used successfully for solving not only this problem, as well as other hard combinatorial optimization problems, since they can […]
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Bingchen Wang, Chenglong Zhang, Lei Song, Lianhe Zhao, Yu Dou, Zihao Yu
DBSCAN is a very classic algorithm for data clus- tering, which is widely used in many fields. However, with the data scale growing much more bigger than before, the traditional serial algorithm can not meet the performance requirement. Recently, parallel computing based on CUDA has developed very fast and has great advantage on big data. […]
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Adam Polak
The clustering coefficient and the transitivity ratio are concepts often used in network analysis, which creates a need for fast practical algorithms for counting triangles in large graphs. Previous research in this area focused on sequential algorithms, MapReduce parallelization, and fast approximations. In this paper we propose a parallel triangle counting algorithm for CUDA GPU. […]
Hanu Hooda, Rainu Nanda
Big Data poses a very great computational challenge for programmers as well as machines as a lot of number crunching is to be done.Due to recent development in the shared memory inexpensive architecture like Graphics Processing Units (GPU), an alternative has emerged. In this paper, we target at decreasing runtime for k-Means, which is one […]
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Seth Hall
Mobile devices offer many new avenues for computer vision and in particular mobile augmented reality applications that have not been feasible with desktop computers. The motivation for this research is to improve mobile augmented reality applications so that natural features, instead of fiducial markers or pure location knowledge, can be used as anchor points for […]
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Ursula Reiterer
Clustering is a basic task in exploratory data analysis. It is used to partition elements of a set into disjoint groups, so-called clusters, such that elements within a group are similar to each other, but dissimilar to elements of other groups. Several clustering algorithms exist, which can be applied depending on the type of dataset […]
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