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Dale Tristram, Karen Bradshaw
General-purpose computation on graphics processing units (GPGPU) has great potential to accelerate many scientific models and algorithms. However, some problems are considerably more difficult to accelerate than others, and it may be challenging for those new to GPGPU to ascertain the difficulty of accelerating a particular problem. Through what was learned in the acceleration of […]
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F. D. Witherden, B. C. Vermeire, P. E. Vincent
PyFR is an open-source high-order accurate computational fluid dynamics solver for mixed unstructured grids that can target a range of hardware platforms from a single codebase. In this paper we demonstrate the ability of PyFR to perform high-order accurate unsteady simulations of flow on mixed unstructured grids using heterogeneous multi-node hardware. Specifically, after benchmarking single-node […]
M. Leeser, S. Mukherjee, J. Brock
Biomedical image reconstruction applications require producing high fidelity images in or close to real-time. We have implemented reconstruction of three dimensional conebeam computed tomography(CBCT) with two dimensional projections. The algorithm takes slices of the target, weights and filters them to backproject the data, then creates the final 3D volume. We have implemented the algorithm using […]
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Alexander Ayriyan, Jan Busa Jr., Eugeny E. Donets, Hovik Grigorian, Jan Pribis
A model of a multilayer device with non-trivial geometrical and material structure and its working process is suggested. The thermal behavior of the device as one principle characteristic is simulated. The algorithm for solving the non-stationary heat conduction problem with a time-dependent periodical heating source is suggested. The algorithm is based on finite difference explicit–implicit […]
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D.William Albert, K.Fayaz, D.Veerabhadra Babu
Apriori-Based algorithms are widely used for association rule mining. However, these algorithms cannot exploit the parallel processing power of modern GPU (Graphics Processing Unit). To make an algorithm to be compatible with GPU, it needs to be changed in representation of data, parallel processing and also in support count. In this paper we propose an […]
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Jennifer Chandler, Harald Obermaier, Kenneth I. Joy
Sets of particles are a frequently used tool for the exploration of time-varying flow fields due to their ease of use and conceptual simplicity. Understanding temporal changes in such particle systems can be difficult with traditional visualization methods such as isosurface rendering and particle splatting. These types of methods only show the current shape of […]
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Newsha Ardalani, Karthikeyan Sankaralingam, Xiaojin Zhu
Heterogeneous processing using GPUs is here to stay and today spans mobile devices, laptops, and supercomputers. Although modern software development frameworks like OpenCL and CUDA serve as a high productivity environment, software development for GPUs is time consuming. First, much work needs to be done to restructure software and data organization to match the GPU’s […]
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Juan P. D'Amato, Marcelo J. Venere
The amount of multimedia information transmitted through the web is very high and increasing. Generally, this kind of data is not correctly protected, since users do not appreciate the amount of information that images and videos may contain. In this work, we present architecture for managing safely multimedia transmission channels. The idea is to encrypt […]
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Oren Segal, Martin Margala, Sai Rahul Chalamalasetti, Mitch Wright
This work presents an effort to bridge the gap between abstract high level programming and OpenCL by extending an existing high level Java programming framework (APARAPI), based on OpenCL, so that it can be used to program FPGAs at a high level of abstraction and increased ease of programmability. We run several real world algorithms […]
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Gordon Inggs, David Thomas, Wayne Luk
We advocate a domain specific software development methodology for heterogeneous computing platforms such as Multicore CPUs, GPUs and FPGAs. We argue that three specific benefits are realised from adopting such an approach: portable, efficient implementations across heterogeneous platforms; domain specific metrics of quality that characterise platforms in a form software developers will understand; automatic, optimal […]
D.William Albert, Dr.K.Fayaz, D.Veerabhadra Babu
Frequent pattern mining is one of the widely used data mining techniques for discovering trends or patterns from databases. As data is growing in exponential pace, data mining activities need more powerful computing. Fortunately modern GPUs (Graphics Processing Units) have specialized electronic circuits and support parallel processing. GPUs are capable of processing huge amount of […]
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Takazumi Matsumoto, Edward Hung, Man Lung Yiu
Outlier detection, also known as anomaly detection, is a common data mining task in identifying data points that are outside expected patterns in a given dataset. It has useful applications such as network intrusion, system faults, and fraudulent activity. In addition, real world data are uncertain in nature and they may be represented as uncertain […]
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