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Czeslaw Smutnicki, Jaroslaw Rudy, Dominik Zelazny
A new and very efficient parallel algorithm for the Fast Non-dominated Sorting of Pareto fronts is proposed. By decreasing its computational complexity, the application of the proposed method allows us to increase the speedup of the best up to now Fast and Elitist Multi-Objective Genetic Algorithm (NSGA-II) more than two orders of magnitude. Formal proofs […]
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Sushil K. Prasad, Michael McDermott, Satish Puri, Dhara Shah, Danial Aghajarian, Shashi Shekhar, Xun Zhou
We summarize the need and present our vision for accelerating geo-spatial computations and analytics using a combination of shared and distributed memory parallel platforms, with general-purpose Graphics Processing Units (GPUs) with 100s to 1000s of processing cores in a single chip forming a key architecture to parallelize over. A GPU can yield one-to-two orders of […]
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Kevin Angstadt, Ed Harcourt
We demonstrate a speedup for database joins using a general purpose graphics processing unit (GPGPU). The technique is novel in that it operates on an SQL virtual machine model developed using CUDA. The implementation compiles an SQL statement to instructions of the virtual machine that are then executed in parallel on the GPU. We use […]
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Paul Harvey, Saji Hameed, Wim Vanderbauwhede
FLEXPART is a popular simulator that models the transport and diffusion of air pollutants, based on the Lagrangian approach. It is capable of regional and global simulation and supports both forward and backward runs. A complex model like this contains many calculations suitable for parallelisation. Recently, a GPU-accelerated version of the simulator (FLEXCPP) has been […]
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Soichiro Ikuno, Susumu Nakata, Yuta Hirokawa, Taku Itoh
High performance computing of Meshless Time Domain Method (MTDM) on multi-GPU using the supercomputer HA-PACS (Highly Accelerated Parallel Advanced system for Computational Sciences) at University of Tsukuba is investigated. Generally, the finite difference time domain (FDTD) method is adopted for the numerical simulation of the electromagnetic wave propagation phenomena. However, the numerical domain must be […]
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Prakash N Ekhande, Sharad A Rumane, Mayur A Ahire
The Segmentation of text from poorly degraded document images is a very hard due to the high intravariation between the document background and the foreground text of different document images. The algorithms used for Image processing take more time for execution on a single core processor. Graphics Processing Unit (GPU) is becoming most popular due […]
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Stanley Tsang
Two well-known bipartite graph matching algorithms, the Gale-Shapley algorithm and the Hungarian (Kuhn-Munkres) algorithm, has been ported to run on General-Purpose Graphics Processing Units (GPGPU) using kernels written with the CUDA programming model. This was done with the goal of characterising and assessing the performance and behaviour of these matching algorithms on the GPU, and […]
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Lan Vu
Current Big Data era is generating tremendous amount of data in most fields such as business, social media, engineering, and medicine. The demand to process and handle the resulting "big data" has led to the need for fast data mining methods to develop powerful and versatile analysis tools that can turn data into useful knowledge. […]
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Ang Li, Hammad Mazhar, Radu Serban, Dan Negrut
ViennaCL is a free open-source linear algebra library for computations on many-core architectures (GPUs, MIC) and multi-core CPUs. The library is written in C++ and supports CUDA, OpenCL, and OpenMP. In addition to core functionality and many other features including BLAS level 1-3 support and iterative solvers, the latest release family ViennaCL 1.6.x provides fast […]
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Sergey Voronin, Per-Gunnar Martinsson
This document describes an implementation in C of a set of randomized algorithms for computing partial Singular Value Decompositions (SVDs). The techniques largely follow the prescriptions in the article "Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions," N. Halko, P.G. Martinsson, J. Tropp, SIAM Review, 53(2), 2011, pp. 217-288, but with some […]
Viktor Kampe, Erik Sintorn, Ulf Assarsson
We present a fast and memory efficient algorithm for generating Compact Precomputed Voxelized Shadows. By performing much of the common sub-tree merging before identical nodes are ever created, we improve construction times by several orders of magnitude for large data structures, and require much less working memory. We also propose a new set of rules […]
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Andre B. Amundsen
Graphic processing units (GPUs) have gained popularity in scientific computing the recent years. This is because of the massive computing power they can provide for parallel tasks, and while GPUs are powerful, it is also hard to fully utilize their power. A part of this difficulty comes from the many parameters available, and tuning of […]
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