检索结果-内蒙古大学图书馆

7th International Conference on Information Science and Control Engineering, ICISCE 2020

作者： Song, Lihui Zhou, Guiyun Chen, Yang Su, Zhonghua University of Electronic Science and Technology of China School of Resources and Environment Chengdu China Beijing Normal University State Key Laboratory of Earth Surface Processes and Resource Ecology Faculty of Geographical Science Beijing China

ISBN: (纸本)9781728164069

The determination of flow directions is an essential step for drainage network extraction, and flat surfaces are common features in flow direction determination. With the challenge of a massive volume of digital elevation models (DEMs), to reduce the running time and memory usage, there is a growing need to develop parallel algorithms to calculate flow directions over flat surfaces. We propose an efficient parallel algorithm for flow directions over flat surfaces based on the existing serial algorithm and three-step parallel framework. The proposed algorithm assigns pre-divided tiles to consumer processes to build local graphs. Then the producer process builds global graphs based on all the local graphs. Finally, consumer processes update the local graphs based on the global graphs and determine flow directions over flat surfaces. For all tested DEMs, the speed-up ratios are greater than 5 with 11 consumer processes. The strong scaling efficiencies are greater than 40% with 11 consumer processes. The proposed algorithm can run generally faster, use less memory, and process massive DEMs that cannot be successfully processed using the existing serial algorithm. This study shows that the proposed algorithm is an ideal parallel algorithm for determining flow direction over flat surfaces in massive DEMs. © 2020 IEEE.

关键词： parallel algorithms

来源：评论

学校读者我要写书评

暂无评论

An Innovative Image-Based Tabular Data Extraction parallel Algorithm 1

引用

2nd International Conference on Computing Analytics and Networking, ICCAN 2019

作者： Behera, Varun Nagesh Jolly Ranjan, Ashish Reza, Motahar High Performance Computing Lab National Institute of Science and Technology Berhampur761008 India

ISBN: (数字)9789811524141

ISBN: (纸本)9789811524134

We propose a novel algorithm for extracting data from images of tabular documents having a specific structure. Our proposed method is able to maintain the original table format and structure, and offers better efficiency over existing methodologies due to its high scalability and parallel architecture. The findings of this paper will increase efficiency in the data extraction process from image-based tabular data and help ease the digitization process of tabular records. © 2020, Springer Nature Singapore Pte Ltd.

关键词： parallel algorithms

来源：评论

学校读者我要写书评

暂无评论

parallel Monte Carlo Simulation of VaR Calculation Based on Intel MIC Architecture

Parallel Monte Carlo Simulation of VaR Calculation Based on ...

引用

2020 International Conference on Big Data and Informatization Education, ICBDIE 2020

作者： Wen, Tiansheng Mao, Rui Tan, Cheng Northwest Af University College of Information Engineering Yangling China

ISBN: (纸本)9781728159003

With regard to the research on financial risk management, Value-at-Risk(VaR) has been widely accepted as a standard approach to financial risk management. There are various ways applicable to calculate VaR, of which Monte Carlo Simulation is regarded as the most effective one to deal with VaR calculation. Nevertheless, the calculation accuracy of the Monte Carlo Simulation method tends to be affected by the scale of simulation. As the scale of simulation increases, the calculation accuracy improves. In the meantime, however, the time cost rises on a continued basis. Therefore, it is difficult for the Monte Carlo Simulation method to be applied in practice. In order to solve this problem, a parallel Monte Carlo Simulation calculation method based on Intel MIC architecture is proposed in this paper to calculate VaR. The simulation process consists of a group of simulation tasks at a time. Due to the absence of data dependency between each simulation task, it is capable of excellent parallelism. In this paper, the OpenMP programming model was applied to assign each simulation task to a different thread for execution. Then, a comparison was performed between the CPU sequential execution scheme, the scheme based on MIC offload mode and the scheme based on MIC native mode. According to the comparative results, the solution based on MIC native mode is superior to that based on MIC offload mode. When the number of times for simulation to be conducted reaches 50,000, the parallel algorithm in MIC native mode achieves a maximum speed-up of 93.2 times compared to CPU sequential calculations, which could make the Monte Carlo Simulation of VaR calculations suitable for practical application. © 2020 IEEE.

关键词： parallel algorithms

来源：评论

学校读者我要写书评

暂无评论

Efficient graphical-processor-unit parallelization algorithm for computing Eigen values

引用

JOURNAL OF ELECTRONIC IMAGING 2020年第6期29卷

作者： Ben Sayadia, Sofien Elloumi, Yaroub Akil, Mohamed Bedoui, Mohamed Hedi Univ Gustave Eiffel CNRS ESIEE Paris Gaspard Monge Comp Sci Lab Marne La Vallee France Univ Monastir Med Technol & Image Proc Lab Fac Med Monastir Tunisia Univ Sousse ISITCom Sousse Tunisia

Several leading-edge applications such as pathology detection, biometric identification, and face recognition are based mainly on blob and line detection. To address this problem, Eigen value computing has been commonly employed due to its accuracy and robustness. However, Eigen value computing requires a raised computational processing, intensive memory data access, and data overlapping, which involve higher execution times. To overcome these limitations, we propose in this paper a new parallel strategy to implement Eigen value computing using a graphics processing unit (GPU). Our contributions are (1) to optimize instruction scheduling to reduce the computation time, (2) to efficiently partition processing into blocks to increase the occupancy of streaming multiprocessors, (3) to provide efficient input data splitting on shared memory to benefit from its lower access time, and (4) to propose new data management of shared memory to avoid access memory conflict and reduce memory bank accesses. Experimental results show that our proposed GPU parallel strategy for Eigen value computing achieves speedups of 27 compared with a multithreaded implementation, of 16 compared with a predefined function in the OpenCV library, and of eight compared with a predefined function in the Cublas library, all of which are performed into a quad core multi-central-processing unit platform. Next, our parallel strategy is evaluated through an Eigen value-based method for retinal thick vessel segmentation, which is essential for detecting ocular pathologies. Eigen value computing is executed in 0.017 s when using Structured Analysis of the Retina database images. Accordingly, we achieved real-time thick retinal vessel segmentation with an average execution time of about 0.039 s. (C) 2020 SPIE and IS&T

关键词： Eigen values Hessian filter parallel algorithms graphics processing unit CUDA real-time graphics processing unit implementation

来源：评论

学校读者我要写书评

暂无评论

parallel algorithm for approximating nash equilibrium in multiplayer stochastic games with application to naval strategic planning 2

Parallel algorithm for approximating nash equilibrium in mul...

引用

AAAI Symposium on the 2nd Workshop on Deep Models and Artificial Intelligence for Defense Applications: Potentials, Theories, Practices, Tools, and Risks, DMAI4DA 2020

作者： Ganzfried, Sam Laughlin, Conner Morefield, Charles Ganzfried Research Arctan Inc.

Many real-world domains contain multiple agents behaving strategically with probabilistic transitions and uncertain (potentially infinite) duration. Such settings can be modeled as stochastic games. While algorithms have been developed for solving (i.e., computing a game-theoretic solution concept such as Nash equilibrium) two-player zero-sum stochastic games, research on algorithms for non-zero-sum and multiplayer stochastic games is limited. We present a new algorithm for these settings, which constitutes the first parallel algorithm for multiplayer stochastic games. We present experimental results on a 4-player stochastic game motivated by a naval strategic planning scenario, showing that our algorithm is able to quickly compute strategies constituting Nash equilibrium up to a very small degree of approximation error. © 2020 CEUR-WS. All rights reserved.

关键词： parallel algorithms

来源：评论

学校读者我要写书评

暂无评论

Hierarchical Model of parallel Metaheuristic Optimization algorithms

引用

Procedia Computer Science 2019年 150卷 441-449页

作者： E.Y. Seliverstov A.P. Karpenko Bauman Moscow State University ul. Baumanskaya 2-ya 5 Moscow 105005 Russia

The paper introduces a novel model of parallel metaheuristic optimization algorithms. The hierarchical graph model of a parallel optimization algorithm is proposed. It consists of the model for a parallel optimization algorithm at the top level of the hierarchy and the model for a sequential optimization algorithm at the bottom level. The unified representation of a metaheuristic optimization algorithm, which allows representing a class of metaheuristic algorithms, is used. The extension of the proposed model to the parametric hierarchical model is proposed. Graph model transformations for a parallel algorithm analysis and synthesis are introduced. The representation of several metaheuristic algorithms with the proposed model is discussed.

关键词： evolutionary algorithms metaheuristic optimization parametric optimization parallel algorithms particle swarm optimization

来源：评论

学校读者我要写书评

暂无评论

New parallel algorithms for finding determinants of NxN matrices

New parallel algorithms for finding determinants of NxN matr...

引用

World Congress on Computer and Information Technologies (WCCIT)

作者： Almalki, Sami Alzahrani, Saeed Alabdullatif, Abdullatif King Saud Univ Coll Comp & Informat Sci Riyadh Saudi Arabia

ISBN: (纸本)9781479904624

Determinants has been used intensively in a variety of applications through history. It also influenced many fields of mathematics like linear algebra. Finding the determinants of a squared matrix can be done using a variety of methods, including well-known methods of Leibniz formula and Laplace expansion which calculate the determinant of any NxN matrix in O(n!). However, decomposition methods, such as: LU decomposition, Cholesky decomposition and QR decomposition, have replaced the native methods with a significantly reduced complexity of O(n boolean AND 3). In this paper, we introduce two parallel algorithms for Laplace expansion and LU decomposition. Then, we analyze them and compare them with their perspective sequential algorithms in terms of run time, speed-up and efficiency, where new algorithms provided better results. At maximum, in Laplace expansion, it became 129% faster, whereas in LU Decomposition, it became 44% faster.

关键词： parallel Processing parallel algorithms Laplace Equations Linear algebra Multithreading

来源：评论

学校读者我要写书评

暂无评论

A computational technique for parallel solution of diagonally dominant banded linear systems

A computational technique for parallel solution of diagonall...

引用

International Conference on High Performance Computing

作者： S. Chandra Sekhara Rao Rabia Kamra Indian Institute of Technology Delhi New Delhi India

ISBN: (纸本)9781665410175

In this work, we present a WZ factorization for a nonsingular diagonally dominant banded matrix. With little modifications in the structures of W and Z, we construct a stable parallel algorithm suitable for solving narrow banded nonsingular diagonally dominant linear systems using divide and conquer technique. Partition the coefficient matrix along the main diagonal; also partition the unknown vector and the right hand side vector accordingly. The coefficient matrix of the ‘reduced system’ which is obtained by collecting the first ß and last ß equations from each partition, where ß is semibadwidth of the given banded linear system, is proved to be nonsingular diagonally dominant. The backward error analysis of the algorithm is presented and the algorithm is proved to be numerically stable. Numerical experiments are conducted to check the performance of the parallel algorithm and to compare the present parallel algorithm with the corresponding subroutines of ScaLAPACK. The performance of the parallel algorithm is evaluated in terms of speedup and scalability.

关键词： Linear systems Error analysis Scalability High performance computing Conferences Partitioning algorithms parallel algorithms

来源：评论

学校读者我要写书评

暂无评论

Unified Structure and parallel algorithms for FBMC Transmitter and Receiver

Unified Structure and Parallel Algorithms for FBMC Transmitt...

引用

IEEE 24th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Zeng, Yonghong Liang, Ying-Chang Chia, Meng Wah Peh, Edward Chu Yeow ASTAR Inst Infocomm Res Singapore 138632 Singapore

ISBN: (纸本)9781467362351

In recent years, filter bank multicarrier (FBMC) has recaptured widespread interests for its possible applications in cognitive radio and dynamic spectrum access. A distinctive feature for cognitive radio is its adaptivity to environment. When environment changes, a cognitive radio will change its parameters to optimize the transmission and receiving. Thus it is desirable to design a unified structure and algorithm for FBMC that needs little change for different parameters. In this paper, we propose a unified structure and parallel algorithms to implement the FBMC. The FBMC system and parallel algorithms are constructed based on the normalized prototype filter. The coefficients of the normalized prototype filter can be pre-computed and stored. The proposed parallel algorithms have the same structure for various choices of time duration, subcarrier spacing and bandwidth. Combined with known parallel algorithms for the fast Fourier transform (FFT), the proposed algorithms fully parallelize the computations for the transmitter and receiver, which can run much faster than conventional serial algorithms as modern processors usually have massive parallel capability.

关键词： parallel algorithms

来源：评论

学校读者我要写书评

暂无评论

Exact parallel Algorithm for the Knapsack Sharing Problem

Exact Parallel Algorithm for the Knapsack Sharing Problem

引用

Electrical, Computer and Energy Technologies (ICECET), International Conference on

作者： Hedi Mhalla Yacine Laalaoui College of Engineering and Technology American University of the Middle East Kuwait College of Computers & Information Technology Taif University Taif KSA

ISBN: (纸本)9781665442329

In the last two decades we observed a considerably improvement in algorithms' performances and their ability to solve hard combinatorial optimization problems. One of these problems is the knapsack sharing problem (KSP). The latter problem is a challenging variant of the well-known NP-hard single knapsack problem. In fact, we can find in the literature several exact and heuristic resolution approaches to solve the (KSP). We mainly propose here an improvement and an adaptation to parallel computing of one of the existing and most recent algorithm in the literature. The approach is a constructive tree search that runs in two phases: the initial solution construction phase and the second phase where we build the optimal solution through a customized branch and bound. We applied a parallel computing on this second phase in order to improve the overall computational time. Finally we present a comparative study on instances from literature to show the positive effect of parallel processing on the computing time.

关键词： Instruction sets Heuristic algorithms Energy resolution parallel algorithms Optimization

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：