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检索条件"主题词=sequential algorithm"

共 131 条记录，以下是91-100 订阅

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Optimizing Simulated Annealing on GPU: A Case Study with IC Floorplanning

Optimizing Simulated Annealing on GPU: A Case Study with IC ...

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12th International Symposium on Quality Electronic Design (ISQED)

作者： Han, Yiding Roy, Sanghamitra Chakraborty, Koushik Utah State Univ Logan UT 84322 USA

ISBN: (纸本)9781612849140

In this paper, we propose a novel floorplanning algorithm based on simulated annealing on GPUs. Simulated annealing is an inherently sequential algorithm, far from the typical programs suitable for Single Instruction Multiple Data (SIMD) style concurrency in a GPU. We propose a fundamentally different approach of exploring the floorplan solution space, where we evaluate concurrent moves on a given floorplan. We illustrate several performance optimization techniques for this algorithm on GPUs. Compared to the sequential algorithm, our techniques achieve 6-160X speedup for a range of MCNC and GSRC benchmarks, while delivering comparable or better solution quality.

关键词： algorithm design and analysis Annealing Benchmark testing GPU Graphics processing unit IC floorplanning algorithm Kernel Simulated annealing Space exploration coprocessors floorplan solution space integrated circuit layout optimizing simulated annealing performance optimization technique sequential algorithm simulated annealing single instruction multiple data style concurrency typical program

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Parallelization of Binary and Real-Coded Genetic algorithms on GPU using CUDA

Parallelization of Binary and Real-Coded Genetic Algorithms ...

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2010 IEEE World Congress on Computational Intelligence

作者： Arora, Ramnik Tulshyan, Rupesh Deb, Kalyanmoy Indian Inst Technol Dept Math & Stat Kanpur 208016 Uttar Pradesh India Indian Inst Technol Dept Engn Mech Kanpur 208016 Uttar Pradesh India

ISBN: (纸本)9781424481262

Genetic algorithms(GAs) are suitable for parallel computing since population members fitness maybe evaluated in parallel. Most past parallel GA studies have exploited this aspect, besides resorting to different algorithms, such as island, single-population master-slave, fine-grained and hybrid models. A GA involves a number of other operations which, if parallelized, may lead to better parallel GA implementation than those currently existing. In this paper, we parallelize binary and real-coded genetic algorithms using CUDA API's with C. Although, objective and constraint violations evaluations are embarassingly parallel, other algorithmic and code optimizations have been proposed and tested. The bottlenecks in a parallel GA implementation are identified and modified suitably. The results are compared with the sequential algorithm on accuracy and clock time for varying problems by studying the effect of a number of parameters, namely: (i) population sizes, (ii) number of threads, (iii) problem sizes, and (iv) problems of differing complexities. Significant speed-ups have been observed over the sequential GA.

关键词： CUDA API GPU application program interfaces computer graphic equipment coprocessors genetic algorithm genetic algorithms parallel algorithms parallel computing sequential algorithm

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Parallel algorithm for Road Points Extraction from Massive LiDAR Data

Parallel Algorithm for Road Points Extraction from Massive L...

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IEEE International Symposium on Parallel and Distributed Processing with Applications

作者： Li, Jiangtao Lee, Hyo Jong Cho, Gi Sung Chonbuk Natl Univ Div Elect & Informat Engn Jeonju South Korea Chonbuk Natl Univ Jeonju South Korea

ISBN: (纸本)9780769534718

Light Detection and Ranging (LiDAR) data has been used to model earth surface in an easy and economic way. As technology is developed the application of LiDAR data is also widely expanded to various areas, such as hydrological modeling, telecommunication service and urban planning. Finding accurate road networks is one of the common applications from massive LiDAR data. A novel algorithm to extract road points has been developed based on both the intensity and height information of data points. First the robustness of the sequential algorithm has been verified with real data points. Then a parallel algorithm has been developed by applying smart area partitioning. The performance of a parallel algorithm showed us a close linear speedup with the use of up to four processors. Experimental results from the parallel algorithm are presented in this paper in detail and demonstrate the robustness of the proposed method.

关键词： Extraction LiDAR Parallel Road Lidar Parallel algorithms Road Parallel Lines sequential algorithm road network

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Power Flow of Multi-Terminal HVDC: Case Study NER Agra UHVDC System 800kV 6000MW 22

Power Flow of Multi-Terminal HVDC: Case Study NER Agra UHVDC...

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22nd National Power Systems Conference (NPSC)

作者： Singh, Nivedita Singh, Chandransh Sood, Yog Raj NIT Hamirpur Hamirpur India

ISBN: (纸本)9781665462020

This paper presents a sequential algorithm for solving ac/dc load flow problem in a MT-HVDC System. The basic advantages of the algorithm used are its simplicity and flexibility when integrated into an already existing power flow package. The computation is very fast and the error accumulated is very low. The dc power flow problem is solved using both Gauss- Seidel and Newton- Raphson methods and comparative results are presented. The test cases that are used are WSCC 3-machine, 9-bus system with a 3-terminal MT-HVDC network being integrated with the already existing ac system. The validity of this algorithm is justified by verifying the results in Dig SILENT Power Factory. The work is furthermore extended by modelling and evaluating power flow of a practical system in form of a case study i.e., NER-Agra HVDC link. It is world's third multi-terminal and first UHVDC project which is designed for +/- 800 kV, 6000 MW. A detailed modelling of this MT-HVDC System is done in order to analyze its power flow.

关键词： sequential algorithm Multi-terminal HVDC Power Flow

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Efficient Computation of Spherical Harmonic Transform using Parallel Architecture of CUDA

Efficient Computation of Spherical Harmonic Transform using ...

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5th International Conference on Signal Processing and Communication Systems (ICSPCS)

作者： Huang, Weiyu Khalid, Zubair Kennedy, Rodney A. Australian Natl Univ Coll Engn & Comp Sci Res Sch Engn Canberra ACT Australia

ISBN: (纸本)9781457711800

Spherical harmonics serve as basis functions on the unit sphere and spherical harmonic transform is required in analysis and processing of signals in the spectral domain. We investigate the possibility of parallel computation of spherical harmonic transform using Compute Unified Device Architecture (CUDA) with no communication between parallel kernels. We identify the parallel components in the widely used spherical harmonic transform method proposed by Driscoll and Healy. We provide the implementation details and compare the computational complexity with the sequential algorithm. For a given bandlimited signal with maximum spherical harmonics degree L, using the O(L) number of parallel processing kernels, we present that the spherical harmonic coefficients can be calculated in O(Llog(2) L) time as compared to O(L-2 log(2) L). For corroboration, we provide the simulation results using CUDA which indicate the reduction in computational complexity

关键词： Parallel architectures spherical harmonic analysis Sphericity complexity classes Transform PARALLEL PROCESSING (COMPUTERS) sequential algorithm Spectral domain Simulation results

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GPU-based Computing of Repeated Range Queries over Moving Objects

GPU-based Computing of Repeated Range Queries over Moving Ob...

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22nd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP)

作者： Silvestri, Claudio Lettich, Francesco Orlando, Salvatore Jensen, Christian S. Univ Ca Foscari Venice Italy Aarhus Univ DK-8000 Aarhus C Denmark

ISBN: (纸本)9781479927289

In this paper we investigate the use of GPUs to solve a data-intensive problem that involves huge amounts of moving objects. The scenario which we focus on regards objects that continuously move in a 2D space, where a large percentage of them also issues range queries. The processing of these queries entails a large quantity of objects falling into the range queries to be returned. In order to solve this problem by maintaining a suitable throughput, we partition the time into ticks, and defer the parallel processing of all the objects events (location updates and range queries) occurring in a given tick to the next tick, thus slightly delaying the overall computation. We process in parallel all the events of each tick by adopting an hybrid approach, based on the combined use of CPU and GPU, and show the suitability of the method by discussing performance results. The exploitation of a GPU allow us to achieve a speedup of more than 20x on several datasets with respect to the best sequential algorithm solving the same problem. More importantly, we show that the adoption of new bitmap-based intermediate data structure we propose to avoid memory access contention entails a 10x speedup with respect to naive GPU based solutions.

关键词： data structures graphics processing units parallel processing query processing 2D space GPU-based computing bitmap-based intermediate data structure data-intensive problem hybrid approach location updates moving objects objects events parallel processing query processing repeated range queries sequential algorithm Computer architecture Graphics processing units Indexes Instruction sets Microprocessors Pipelines Synchronization bitmap gpgpu gpu workload distribution lock-free data structures moving objects repeated range queries uniform grids

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Technique for the algorithms formulae investigation

Technique for the algorithms formulae investigation

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International Conference on Modern Problems of Radio Engineering, Telecommunications and Computer Science (TCSET 2004)

作者： Dragan, Y Ovsyak, V Sikora, L Lviv Politech Natl Univ UA-79013 Lvov Ukraine

A technique of algorithms formulae investigation which has been developed on the ground off mathematical induction is described.

ISBN: (纸本)9665533800

A technique of algorithms formulae investigation which has been developed on the ground off mathematical induction is described.

关键词： algorithm formula of algorithm sequential algorithm investigation of algorithm mathematical induction

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Less is More: Video Trimming for Action Recognition

Less is More: Video Trimming for Action Recognition

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IEEE International Conference on Computer Vision (ICCV)

作者： Antic, Borislav Milbich, Timo Ommer, Bjoern Heidelberg Univ Heidelberg Collaboratory Image Proc D-69115 Heidelberg Germany

ISBN: (纸本)9781479930227

Action recognition is an important precursor for understanding human activities in videos. The current paradigm of action recognition is to classify a video sequence as a whole. However, actions usually occur only in part of a video sequence, rendering the rest of the video irrelevant for action recognition. In this paper, we propose a method for learning a subsequence classifier which can detect and classify part of a video that corresponds to the action. The subsequence classifier is trained from weakly labeled training videos whose subsequence labels are not provided, but need to be inferred during learning. We use the framework of multiple instance learning to solve two problems jointly: i) find the action subsequences in training videos, ii) train the subsequence classifier using the inferred action subsequences. To obtain a robust solution to the MIL problem, we propose a sequential algorithm that consecutively decreases the number of inferred action subsequences per video and trims their length until only one short subsequence is used as the action representative in each video. We evaluate the combination of the automatically trained subsequence classifier and the full sequence classifier on the very challenging Hollywood2 benchmark set and observe a significant gain in the performance over the baseline full sequence classifier. Moreover, a favorable performance of the subsequence classifier for temporal localization of actions in videos is evidenced on two categories of the Hollywood2 dataset.

关键词： action recognition multiple instance learning video analysis Videotapes Classifiers Video sequences Action trimmings VIDEO ANALYSIS Training Videos Recognition (Psychology) sequential algorithm Robust solution

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Geodetic Iterative Methods for Nonlinear Acoustic Sources Localization: Application to Cracks Effects Detected with Acoustic Emission 6

Geodetic Iterative Methods for Nonlinear Acoustic Sources Lo...

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6th International Workshop of NDT Experts on NDT in Progress

作者： Zavesky, Michal Kus, Vaclav Czech Tech Univ Fac Nucl Sci & Phys Engn Dept Math Trojanova 13 Prague 12000 EU Czech Republic

ISBN: (纸本)9788021443396

This paper is related to Acoustic Emission (AE) principle, which is a Nondestructive Testing method (NDT) for structural health monitoring and many other applications. We deal with the geodetic curve based localization of the defects on surfaces of solid bodies mathematically described as a conjunction of several simpler parametrized shapes like cylinders, toroids, spheres, cones,... with intersections. We demonstrate a numerical solution of geodesic equations by the algorithm NewtonRaphson method. For faster computations we propose a few improvements using sequential algorithm applied to bisected points of the intersections, which is compared with trivial Fundamental method. The whole algorithm for finding geodesics on combined surfaces is applied to virtual testing body which was designed according to the solid watering can.

关键词： Acoustic emission geodetic curve geodesic equations Newton-Raphson method sequential algorithm

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A GPU Implementation of Parallel Constraint-based Local Search

A GPU Implementation of Parallel Constraint-based Local Sear...

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22nd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP)

作者： Arbelaez, Alejandro Codognet, Philippe Natl Univ Ireland Univ Coll Cork INSIGHT Ctr Data Analyt Corcaigh Ireland Univ Tokyo Dept Comp Sci UPMC JFLICNRS Tokyo 1138654 Japan

ISBN: (纸本)9781479927289

In this paper we study the performance of constraint-based local search solvers on a GPU. The massively parallel architecture of the GPU makes it possible to explore parallelism at two different levels inside the local search algorithm. First, by executing multiple copies of the algorithm in a multiwalk manner and, second, by evaluating large neighborhoods in parallel in a single-walk manner. Experiments on three well-known problem benchmarks indicate that the current GPU implementation is up to 17 times faster than a well-tuned sequential algorithm implemented on a desktop computer.

关键词： graphics processing units parallel architectures search problems GPU massively parallel architecture parallel constraint-based local search sequential algorithm Benchmark testing Graphics processing units Instruction sets Memory management Optimized production technology Random access memory Search problems CSP GPU Local Search

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