In this paper, we propose a parallel algorithm for H.264/AVC deblocking filter which is scalable to the number of processors. Unlike the conventional approach, which is limited by the independent data units, the desig...
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ISBN:
(纸本)9781424410163
In this paper, we propose a parallel algorithm for H.264/AVC deblocking filter which is scalable to the number of processors. Unlike the conventional approach, which is limited by the independent data units, the designed algorithm allows issuing dependent data units concurrently to decrease the penalty from synchronization of data units. For the general-purpose dual-core processors, experimental results show that our method speeds up 1.72 and 1.39 times as compared with optimized sequential method and the well-known wavefront parallelizing method, respectively.
Network virtualization is ubiquitously an essential attribute to enable the success of the future virtualized networks (e.g. forthcoming 5G network, smart Internet of Things (IoT)). Virtual Network Embedding (VNE) is ...
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ISBN:
(纸本)9781538640883
Network virtualization is ubiquitously an essential attribute to enable the success of the future virtualized networks (e.g. forthcoming 5G network, smart Internet of Things (IoT)). Virtual Network Embedding (VNE) is the main challenge in network virtualization that allows multiple heterogeneous Virtual Networks (VNs) to simultaneously coexist on top of a shared substrate infrastructure. Many VNE algorithms have been proposed over past decades but most of them are merely focusing on VNE node mapping and leaving link mapping task for the popular k-shortest path algorithms or multi-commodity flow (MCF) mechanism. In this paper, we propose an intelligent VNE orchestration for link mapping stage which exploits distributed parallelism to considerably reduce the processing time with high efficiency. Extensive simulations have shown that our proposed algorithm outperforms the most popular VNE algorithms.
In order to make the concurrency, synchronism function of Petri nets system capable of parallel control and Simulation Implementation, proposed Petri network switching system, function partition method based on Multi-...
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ISBN:
(纸本)9781467365932
In order to make the concurrency, synchronism function of Petri nets system capable of parallel control and Simulation Implementation, proposed Petri network switching system, function partition method based on Multi-core PC. Firstly, according to the Petri nets system of parallel process and its principle, analysis of advanced Petri nets and P/T network algebra model and its inner mechanism, Given the process and theory verification of advanced Petri nets into P/T nets;Based on the network model Formalization and Color Petri nets correlation matrix pretreatment, proposed colored Petri nets into P/T nets algorithm. Then, P/T nets function division according to invariable Place technique, classification into subnets having different functions (process), analysis and expansion of the P/T nets system process conditions, and gives examples of authentication, Get P/T nets functional partitioning algorithm based on non-negative invariable Place;On this basis, Research process concurrency, synchronization parallel with implementation, put forward Petri nets parallel algorithm based on Multi-core PC, Given Petri nets parallel algorithms and application examples In the environment of Multi-core PC. Experimental results show that, Petri nets parallel algorithms based on Multi-core PC let Petri nets system to better reflect the actual running, and Is an effective method to achieve Petri net system parallel control and simulation run.
The goal of this paper is to develop a parallel algorithm that, on input of a learning sample, identifies a regular language by means of a nondeterministic finite automaton (NFA). A sample is a pair of finite sets con...
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ISBN:
(纸本)9781728189468
The goal of this paper is to develop a parallel algorithm that, on input of a learning sample, identifies a regular language by means of a nondeterministic finite automaton (NFA). A sample is a pair of finite sets containing positive and negative examples. Given a sample, a minimal NFA or the range of possible sizes of such an NFA, that represents the target regular language is sought. We define the task of finding an NFA, which accepts all positive examples and rejects all negative ones, as a constraint satisfaction problem, and then propose a parallel algorithm to solve the problem. The results of computational experiments on the variety of test samples are reported.
The paper deals with the problem of analyzing fault, susceptibility of a parallel algorithm designed for multiprocessor array (MIMD structure). This algorithm realizes quite complex communication protocol in the syste...
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ISBN:
(纸本)0769517307;0769517315
The paper deals with the problem of analyzing fault, susceptibility of a parallel algorithm designed for multiprocessor array (MIMD structure). This algorithm realizes quite complex communication protocol in the system. We present an original methodology of the analysis based on the use of software implemented fault injector. The considered algorithm is modeled as a multithreaded application. The experiment set up an I results are presented and commented The performed experiments proved relatively high natural robustness of the analyzed algorithm and showed further possibilities of its improvement.
For the high time overhead problems of Apriori algorithm while solving for the long length frequent patterns, using the MapReduce distributed programming ideas, the paper breaks the original idea of Aproiri which disc...
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ISBN:
(纸本)9781479941698
For the high time overhead problems of Apriori algorithm while solving for the long length frequent patterns, using the MapReduce distributed programming ideas, the paper breaks the original idea of Aproiri which discovers the frequent item sets through gradually increasing the element numbers in the frequent item sets. It proposes a new non-iteration parallel algorithm about frequent pattern discovery, which can get arbitrary length frequent pattern at random. The experimental results show that the proposed algorithm has better time performance than such parallel algorithms which are under the ideas of traditional Apriori algorithm.
In a disaster field, to obtain the optimal path in unknown environment,a rescue robot needs to build an environment map. Sensors mounted on the robots cooperate to monitor the environment, the information of the disas...
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ISBN:
(纸本)9783037851579
In a disaster field, to obtain the optimal path in unknown environment,a rescue robot needs to build an environment map. Sensors mounted on the robots cooperate to monitor the environment, the information of the disaster field is collected by the sonsors of different robots, all signal from sensors (mounted on all robots and signal form GPS) are sent to the bakeside parllel processors with wireless network. A grid computing environment serves as the backside parallel processors with Globus Toolkit, the grid computing processor process all the signals and construct the global map to help robot for navigation path *** rescue robot get control signal from the grid computing processor with wireless network,thus, the robot is not necessary to be sophisticated. New computing methods are given for parallel algorithm on grid *** experiments show that the method is more practical and helps the path planning problem to be solved more efficiently, the advantages of large seale computing on grid are shown.
The tomographic reconstruction is a powerful diagnostic tool in nuclear fusion experiments for the determination of the shape and position of the plasma. However, neural networks are emerging as a suitable alternative...
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The tomographic reconstruction is a powerful diagnostic tool in nuclear fusion experiments for the determination of the shape and position of the plasma. However, neural networks are emerging as a suitable alternative to conventional plasma tomography algorithms. In order to train such AI/ML based models, we need large-scale, diversified image data for learning and evaluation which is difficult to obtain from real experiments. Accuracy and real-time response is also critical, therefore in this article we propose an effective shared memory based parallel algorithm for synthetic imaging diagnostic data generation. The practicality of the proposed parallel algorithm has been evaluated experimentally by comparing it to the sequential algorithm on two different computing architectures. We observe a maximum speedup of 21 at 32 threads and demonstrate that our proposed parallel algorithm scales well over a range of image sizes. The proposed parallel algorithm can be used to obtain the synthetic images within a few seconds which is very important for real time applications. We also provide an analysis on the importance of choosing the right scheduling type and optimum chunk size to obtain the maximum speedup.
The permutation generation method is based on starter sets generation under exchange operation and exploited it for listing down all n! Permutations. However permutation generation is time consuming process, the imple...
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ISBN:
(纸本)9780735412361
The permutation generation method is based on starter sets generation under exchange operation and exploited it for listing down all n! Permutations. However permutation generation is time consuming process, the implementation of sequential algorithm to parallel computation is the option for reducing the computation time. The sequential algorithm is implemented to a parallel algorithm by integrating with Message Passing Interface (MPI) libraries by parallelizing the starter sets generation task. The speedup and efficiency is the indicator tool for analyzing performance of this parallel algorithm. The results show reduction time computation of parallel algorithm among processors.
parallel computing is an important method used in high performance computing. A new SIMD architecture named ESCA (Engineering and Science Computing Accelerator) is introduced briefly in this paper. It aims to accelera...
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ISBN:
(纸本)9781424474561
parallel computing is an important method used in high performance computing. A new SIMD architecture named ESCA (Engineering and Science Computing Accelerator) is introduced briefly in this paper. It aims to accelerate the computation for most critical scientific workload as a coprocessor by virtue of outstanding architecture and flexible parallel algorithm. As dense matrix multiplication is a widely used operation that can be accelerated by parallel computing, we maps its algorithm onto ESCA and estimates the performance, and the results imply that ESCA has some advantage and potentiality.
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