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检索条件"主题词=Parallel algorithm"

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On the Effectiveness of Using the GPU for Numerical Solution of Stochastic Collection Equation

On the Effectiveness of Using the GPU for Numerical Solution...

引用

13th International Conference on Computational Science and Its Applications (ICCSA)

作者： Raba, Nikita O. Stankova, Elena N. St Petersburg State Univ St Petersburg 198504 Russia

ISBN: (纸本)9783642396403

Effective parallel algorithm is presented for numerical solution of stochastic collection equation on graphical processors. System of stochastic collection equations describes evolution of spectrum of drops and ice crystals due to the process of coalescence in the numerical models of natural convective clouds. They present the most computationally expensive part of such models aimed for forecasting dangerous weather phenomena such as thunderstorm, heavy rain and hail. Our results show that use of GPU can accelerate calculations in 15-20 times and thus provide operational forecast of such disaster events. parallel algorithm is specially developed for calculations on GPU using CUDA technology. It is quadratic in time and allows using more than 1000 threads for effective parallelization. Special methods for optimization of memory access are also described.

关键词： parallel algorithm GPU CUDA technology stochastic collection equation numerical modeling

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parallel Communication-Free algorithm for Triangular Matrix Inversion on Heterogenoues Platform

Parallel Communication-Free Algorithm for Triangular Matrix ...

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Federated Conference on Computer Science and Information Systems (FedCSIS)

作者： Mahfoudhi, Ryma Mahjoub, Zaher Nasri, Wahid Univ Tunis El Manar Fac Sci Tunis Manar 2 Tunis 2092 Tunisia Higher Sch Sci & Techn Tunis Tunis 1008 Tunisia

ISBN: (纸本)9788360810484

We address in this paper the parallelization of a recursive algorithm for triangular matrix inversion (TMI) based on the 'Divide and Conquer' (D&C) paradigm. A series of different versions of an original sequential algorithm are first presented. A theoretical performance study permits to establish an accurate comparison between the designed algorithms. Afterwards, we develop an optimal parallel communication-free algorithm targeting a heterogeneous environment involving processors of different speeds. For this purpose, we use a non equitable and incomplete version of the D&C paradigm consisting in recursively decomposing the original TMI problem in two subproblems of non equal sizes, then decomposing only one subproblem and so on. The theoretical study is validated by a series of experiments achieved on two platforms, namely an 8-core shared memory machine and a distributed memory cluster of 16 nodes. The obtained results permit to illustrate the interest of the contribution.

关键词： communication free divide and conquer heterogeneous platform parallel algorithm recursive algorithm triangular matrix inversion

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A parallel EAX-based algorithm for minimizing the number of routes in the vehicle routing problem with time windows

A parallel EAX-based algorithm for minimizing the number of ...

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14th IEEE International Conference on High Performance Computing and Communications (HPCC) / IEEE 9th International Conference on Embedded Software and Systems (ICESS)

作者： Blocho, Miroslaw Czech, Zbigniew J. Silesia Univ Technol Gliwice Poland

ISBN: (纸本)9780769547497

A parallel EAX-based algorithm for minimizing the number of routes in the vehicle routing problem with time windows is presented. The main contribution is a novel approach concerning the usage of the edge assembly crossover (EAX) operator during exchanging the best solutions between the processes. The objective of the work is to analyze the speedup, achieved accuracy of solutions and scalability of the MPI implementation. For comparisons the selected Gehring and Homberger's (GH) tests are used. The results of the extensive computational experiments indicate that the new algorithm based on the EAX approach is not only very fast but also very effective. The eight new best-known solutions for the GH benchmarking tests were found by making use of the algorithm.

关键词： parallel algorithm vehicle routing problem with time windows guided local search metaheuristics EAX operator MPI library

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GPU-Accelerated Adaptive Compression Framework for Genomics Data

GPU-Accelerated Adaptive Compression Framework for Genomics ...

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IEEE International Conference on Big Data (Big Data)

作者： Guo, GuiXin Qiu, Shuang Ye, ZhiQiang Wang, BingQiang Fang, Lin Lu, Mian See, Simon Mao, Rui BGI Shenzhen Shenzhen Peoples R China ASTAR Inst HPC Singapore Singapore BGI NVIDIA Joint Innovat Lab Shenzhen Peoples R China Shenzhen Univ Guangdong Prov Key Lab Popular High Performance C Shenzhen Peoples R China

ISBN: (纸本)9781479912926;9781479912933

Genomics data is being produced at an unprecedented rate, especially in the context of clinical applications and grand challenge questions. There are various types of data in genomics research, most of which are stored as plain text tables. A data compression framework tailored to this file type is introduced in this paper, featuring a combination of generic compression algorithms, GPU acceleration, and column-major storage. This approach is the first to achieve both compression and decompression rates of around 100MB/s on commodity hardware without compromising compression ratio. By selecting appropriate compression schemes for each column of data, this framework efficiently exploits data redundancy while remaining applicable to a wide range of formats. The GPU-accelerated implementation also properly exploits the parallelism of compression algorithms. Finally, this paper presents a novel first-order Markov model based transformation, with evidence that it is at least as effective as Burrows-Wheeler and Move-To-Front in some contexts.

关键词： big data GPU data compression parallel algorithm Markov model

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A Peta-scalable CPU-GPU algorithm for Global Atmospheric Simulations 13

A Peta-scalable CPU-GPU Algorithm for Global Atmospheric Sim...

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18th ACM SIGPLAN Symposium on Principles and Practice of parallel Programming

作者： Yang, Chao Xue, Wei Fu, Haohuan Gan, Lin Li, Linfeng Xu, Yangtong Lu, Yutong Sun, Jiachang Yang, Guangwen Zheng, Weimin Chinese Acad Sci Inst Software Beijing Peoples R China Tsinghua Univ Dept Comp Sci & Technol Beijing 100084 Peoples R China Tsinghua Univ Minist Educ Key Lab Earth Syst Modeling Beijing 100084 Peoples R China Tsinghua Univ Ctr Earth Syst Sci Beijing 100084 Peoples R China Natl Univ Def Technol Dept Comp Sci & Technol Changsha Hunan Peoples R China Chinese Acad Sci State Key Lab Space Weather Beijing Peoples R China

ISBN: (纸本)9781450319225

Developing highly scalable algorithms for global atmospheric modeling is becoming increasingly important as scientists inquire to understand behaviors of the global atmosphere at extreme scales. Nowadays, heterogeneous architecture based on both processors and accelerators is becoming an important solution for large-scale computing. However, large-scale simulation of the global atmosphere brings a severe challenge to the development of highly scalable algorithms that fit well into state-of-the-art heterogeneous systems. Although successes have been made on GPU-accelerated computing in some top-level applications, studies on fully exploiting heterogeneous architectures in global atmospheric modeling are still very less to be seen, due in large part to both the computational difficulties of the mathematical models and the requirement of high accuracy for long term simulations. In this paper, we propose a peta-scalable hybrid algorithm that is successfully applied in a cubed-sphere shallow-water model for global atmospheric simulations. We employ an adjustable partition between CPUs and GPUs to achieve a balanced utilization of the entire hybrid system, and present a pipe-flow scheme to conduct conflict-free inter-node communication on the cubed-sphere geometry and to maximize communication-computation overlap. Systematic optimizations for multithreading on both GPU and CPU sides are performed to enhance computing throughput and improve memory efficiency. Our experiments demonstrate nearly ideal strong and weak scalabilities on up to 3,750 nodes of the Tianhe-1A. The largest run sustains a performance of 0.8 Pflops in double precision (32% of the peak performance), using 45,000 CPU cores and 3,750 GPUs.

关键词： parallel algorithm atmospheric modeling GPU heterogeneous system communication-computation overlap scalability

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parallelization of KMP String Matching algorithm

Parallelization of KMP String Matching Algorithm

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World Congress on Computer and Information Technologies (WCCIT)

作者： Alzoabi, Ubaid S. Alosaimi, Naser M. Bedaiwi, Abdullah S. Alabdullatif, Abdullatif M. King Saud Univ Coll Comp & Informat Sci Dept Comp Sci Riyadh Saudi Arabia

ISBN: (纸本)9781479904624

Knuth Morris-Pratt (KMP) algorithm is one of the most popular strings searching algorithm. The parallelism of KMP is one of research topic over last two years. In our paper we simulated two current parallel algorithms with our new proposed parallel algorithm. Our simulation result presents improvement of our proposed parallel algorithm.

关键词： component KMP algorithm String matching parallelism parallel algorithm

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parallelizing Dynamic Time Warping algorithm Using Prefix Computations on GPU

Parallelizing Dynamic Time Warping Algorithm Using Prefix Co...

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15th IEEE International Conference on High Performance Computing and Communications (HPCC) /11th IEEE/IFIP International Conference on Embedded and Ubiquitous Computing (EUC)

作者： Xiao, Limin Zheng, Yao Tang, Wenqi Yao, Guangchao Ruan, Li State Key Lab Software Dev Environm Beijing 100191 Peoples R China Beihang Univ Sch Comp Sci & Engn Beijing 100191 Peoples R China

ISBN: (纸本)9780769550886

The dynamic time warping (DTW) algorithm has O(n(2)) time complexity, which indicates that it is hard to process large-scale time series within an acceptable time. Recently, many researchers have used graphics processing units (GPUs) to accelerate the algorithm. Owing to the data dependence of DTW, however, most of existing GPU-based DTW algorithms exploits task-level parallelism by simply replicating the serial algorithm on every multiprocessor of a GPU. The fundamental issue with such coarse-grained parallelism is that the solvable problem size is severely limited by the share memory and cache of a GPU multiprocessor. In this study, we introduce a specific transformation of data dependence by using prefix computations. Further, we propose an efficient GPU-parallel DTW algorithm to address the problem of instance sizes limitation. The efficiency of our algorithm is validated through experiments, which demonstrate improved performance over existing GPU-based task-level parallel DTW algorithms. Our experimental results indicate speedups up to 99 times faster on NVIDIA GTX480, compared to CPU implementations.

关键词： dynamic time warping parallel algorithm prefix computations GPU CUDA

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Research on algorithm for Mining Frequent Itemsets Based on Cloud Computing

Research on Algorithm for Mining Frequent Itemsets Based on ...

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International Conference on Measurement, Instrumentation and Automation (ICMIA 2012)

作者： Huang Shu Zhuang Li Tao Shen Luo Dan Qinzhou Univ Math & Comp Sci Inst Qinzhou Peoples R China Sch Comp & Elect Informat Guangxi Univ Nanning Peoples R China

ISBN: (纸本)9783037855454

This thesis aims to discuss the problems now existing in mining probabilistic of MapReduce Apriori, and to put forward an algorithm about mining probabilistic frequent itemsets based on cloud computing. This algorithm proposes to reduce the quantity of candidate item sets by the strategy of designing to decrease candidate item sets, and divide data sets and candidate item sets into related nodes in order to minimize candidate item sets. By compressing the transaction set to accomplish connecting optimization, it can avoid producing massive alternatives item sets in the process of self-link to improve the operation efficiency of algorithm.

关键词： cloud computing association rule parallel algorithm mapReduce apriori

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Detecting Spurious Counterexamples Efficiently in Abstract Model Checking 13

Detecting Spurious Counterexamples Efficiently in Abstract M...

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35th International Conference on Software Engineering (ICSE)

作者： Tian, Cong Duan, Zhenhua Xidian Univ ICTT & ISN Lab Xian 710071 Peoples R China

ISBN: (纸本)9781467330763

The Abstraction is one of the most important strategies for dealing with the state space explosion problem in model checking. With an abstract model, the state space is largely reduced, however, a counterexample found in such a model that does not satisfy the desired property may not exist in the concrete model. Therefore, how to check whether a reported counterexample is spurious is a key problem in the abstraction-refinement loop. Particularly, there are often thousands of millions of states in systems of industrial scale, how to check spurious counterexamples in these systems practically is a significant problem. In this paper, by re-analyzing spurious counterexamples, a new formal definition of spurious path is given. Based on it, efficient algorithms for detecting spurious counterexamples are presented. By the new algorithms, when dealing with infinite counterexamples, the finite prefix to be analyzed will be polynomially shorter than the one dealt by the existing algorithm. Moreover, in practical terms, the new algorithms can naturally be parallelized that makes multi-core processors contributes more in spurious counterexample checking. In addition, by the new algorithms, the state resulting in a spurious path (false state) that is hidden shallower will be reported earlier. Hence, as long as a false state is detected, lots of iterations for detecting all the false states will be avoided. Experimental results show that the new algorithms perform well along with the growth of system scale.

关键词： model checking formal verification abstraction refinement parallel algorithm

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ParSA: parallel Simulated Annealing Placement algorithm for Multi-core Systems

ParSA: Parallel Simulated Annealing Placement Algorithm for ...

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16th CSI International Symposium on Computer Architectures and Digital Systems (CADS)

作者： Sanjabi, Mercedeh Jahanian, Ali Amanollahi, Saba Miralaei, Negar Islamic Azad Univ Qazvin Branch Elect Comp & Biomed Eng Dept Qazvin Iran Shahid Beheshti Univ Dept Elect & Comp Engn Tehran Iran

ISBN: (纸本)9781467314824;9781467314817

Simulated annealing is known as a widely used algorithm for complex and nonlinear combinatorial optimization problems. This technique has been applied to variety of the problems such as VLSI cell placement. However, simulated annealing placement requires long execution time to brows the search space and find the near-optimal solution. There were many attempts to parallelize it on multi-processor systems but addressed algorithms results in poor speedup due to considerable communication overhead between the processors. In this paper, we proposed a new parallel Simulated Annealing based on multi-core systems with very low communication overhead. Experimental results show the speedup of the proposed algorithm is improved by 32% on average without considerable quality degradation.

关键词： Multi-core systems parallel algorithm Placement

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