In the paper the task of concurrent analysis of a Petri net is considered. A Petri net is given, and several processes able to simulate transition firings. The methods of analysis described in this paper are based on ...
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ISBN:
(纸本)0769517307;0769517315
In the paper the task of concurrent analysis of a Petri net is considered. A Petri net is given, and several processes able to simulate transition firings. The methods of analysis described in this paper are based on the original approach to net decomposition and oriented for the so-called operational nets and a class of cyclic Petri nets. The methods analyze the nets by reduced state space constructing;both their sequential and parallel versions are described. Also the algorithm of decomposition oriented to concurrent analysis is described. The suggested methods of analysis can be implemented as a multithread application.
PVM and MPI, two systems for programming clusters, are often compared. The comparisons usually start with the unspoken assumption that PVM and MPI represent different solutions to the same problem. In this paper we sh...
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ISBN:
(纸本)0769517455
PVM and MPI, two systems for programming clusters, are often compared. The comparisons usually start with the unspoken assumption that PVM and MPI represent different solutions to the same problem. In this paper we show that, in fact, the two systems often are solving different problems. In cases where the problems do match but the solutions chosen by PVM and MPI are different, we explain the reasons for the differences. Usually such differences can be traced to explicit differences in the goals of the two systems, their origins, or the relationship between their specifications and their implementations. For example, we show that the requirement for portability and performance across many platforms caused MPI to choose approaches different from those made by PVM, which is able to exploit the similarities of network-connected systems.
On the basis of analysis to the thermal process of power plant and simple genetic algorithm, a improved genetic algorithm is introduced to optimize controller parameters of thermal process. In the genetic algorithm, f...
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ISBN:
(纸本)7506255715
On the basis of analysis to the thermal process of power plant and simple genetic algorithm, a improved genetic algorithm is introduced to optimize controller parameters of thermal process. In the genetic algorithm, floating-point genes, rank-based model, elitist model and parallel algorithm are used. The premature convergence is eliminated, the global and local searching ability is improved. The MATLAB program of genetic algorithm of controller parameters optimization is given. A single loop PID control system and a superheat steam control system is optimized and optimal parameters are given. It is shown by simulation research that the genetic algorithm is better than traditional methods, satisfactory, control results can be got with the optimized parameters.
We present a new parallelization technique that significantly improves performance of certain data-parallel algorithms on heterogeneous clusters of workstations. The two main goals of our technique are to improve exec...
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ISBN:
(纸本)0769517455
We present a new parallelization technique that significantly improves performance of certain data-parallel algorithms on heterogeneous clusters of workstations. The two main goals of our technique are to improve execution times (compared to traditional parallelization techniques) and to efficiently use the computing resources available in the cluster. The technique is based on a pre-processing phase where information about the cluster is obtained, a load balanced data decomposition is derived, and information is generated to guide the cluster node utilization during the execution of the parallel algorithm. We applied our technique to Gaussian Elimination and Pairwise Interaction Problems, the experiments show speedup improvements up to 133% and 275% respectively and the cluster utilization efficiency improves up to 180% and 300% when compared to traditional parallelization techniques.
In this paper, we propose a new method for the computation of the algorithm of robust Q-mode principal component analysis (RQMPCA) used in statistics. We will show how we can reduce the computation complexity of this ...
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ISBN:
(纸本)0769516262
In this paper, we propose a new method for the computation of the algorithm of robust Q-mode principal component analysis (RQMPCA) used in statistics. We will show how we can reduce the computation complexity of this algorithm by p, where p is the number of variables. An application, on web document retrieval time, was studied using this algorithm. We will report some statistical results on retrieval time and its relationship with document's size and its number of objects.
In this paper, we first present theoretical results, helping to understand the unfolding algorithm presented in [6,7]. We then propose a modification of this algorithm, which can be efficiently parallelised and admits...
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ISBN:
(纸本)3540434194
In this paper, we first present theoretical results, helping to understand the unfolding algorithm presented in [6,7]. We then propose a modification of this algorithm, which can be efficiently parallelised and admits a more efficient implementation. Our experiments demonstrate that the degree of parallelism is usually quite high and resulting algorithms potentially can achieve significant speedup comparing with the sequential case.
This paper presents part of the work being carried out to obtain parallel versions of the main SLICOT routines for model reduction. It is focused on the parallel solution of standard Lyapunov equations obtaining the C...
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This paper presents part of the work being carried out to obtain parallel versions of the main SLICOT routines for model reduction. It is focused on the parallel solution of standard Lyapunov equations obtaining the Cholesky factor of the controllability and observability Grammians. This operation is an important basis for model reduction methods. Routines from the standard libraries BLAS, LAPACK, SLICOT, PBLAS and ScaLAPACK have been used whenever possible in the parallelisation process. However, it has been necessary to develop some new routines. Experimental results obtained using a cluster of PC's are shown.
An efficient parallel approach for the computation of the eigenvalue of smallest absolute magnitude of sparse real and complex matrices is provided. The proposed strategy tries to improve the efficiency of the reverse...
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An efficient parallel approach for the computation of the eigenvalue of smallest absolute magnitude of sparse real and complex matrices is provided. The proposed strategy tries to improve the efficiency of the reverse power method. At each inverse power iteration the linear system is solved either by the conjugate gradient scheme (symmetric case) or by the Bi-CGSTAB method (symmetric case). Both solvers are preconditioned employing the approximate inverse factorization and thus are easily parallelized. The satisfactory speed-ups obtained on the CRAY T3E supercomputer show the high degree of parallelization reached by the proposed algorithm.
This paper introduces the developing situation of decision tree during several years. During these years, ID3 algorithm has been in the highest flight in decision tree. ID3 makes use of information entropy as heuristi...
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ISBN:
(纸本)0780375084
This paper introduces the developing situation of decision tree during several years. During these years, ID3 algorithm has been in the highest flight in decision tree. ID3 makes use of information entropy as heuristic to select "excellent attribution" at each node, so it can get smaller depth but not the proper width of the tree. That is to say that if the width is large, no matter what small of decision tree is, the leaf node will not be small. It is very important that smaller nodes get higher classify precision for decision tree. This paper provides two algorithms, which can avoid the deficiency of ID3 and reduce the width of the tree to get the better result, the one is PID based on probability, and the other one is EMID based on entropy.
When dealing with high‐frequency time series, statistical procedures giving reliable estimates of unknown parameters and forecasts in real time are required. This is why recursive estimation methods are usually prefe...
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