Metaheuristics are very useful methods because they can find (approximate) solutions of a great variety of problems. One of them, which interests us, is graph partitioning. We present a new metaheuristic based on nucl...
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ISBN:
(纸本)9781424400546
Metaheuristics are very useful methods because they can find (approximate) solutions of a great variety of problems. One of them, which interests us, is graph partitioning. We present a new metaheuristic based on nuclear fusion and fission of atoms. This metaheuristic, called fusion fission, is compared to other classical algorithms. First, we present spectral and multilevel algorithms which are used to solve partitioning problems. Secondly, we present two metaheuristics applied to partitioning problems: simulated annealing and ant colony algorithms. We show that fusion fission gives good results, compared to the other algorithms. We demonstrate on a problem of air traffic control that metaheuristics methods can give better results than specific methods
The following topics are dealt with: parallel computing; distributed computing; interconnection networks; communication and telecommunication; imageprocessing and computer graphics; access control and authorization; ...
The following topics are dealt with: parallel computing; distributed computing; interconnection networks; communication and telecommunication; imageprocessing and computer graphics; access control and authorization; wireless networks and mobile computing; database applications and data mining; parallelizing compilers; parallel/distributed architectures; intelligent computing and neural networks; Internet computing; network routing and communication algorithms; Web technologies; ubiquitous computing systems; task mapping and job scheduling; security protocols; computer networks; formal methods and programming languages; intrusion detection and survivability; grid computing systems; applied cryptography; P2P and ad hoc networks; and reliability and fault-tolerance
This paper presents a new generalized particle model (GPM) to generate the prediction coding for lossless data compression. Local rules for particle movement in GPM, parallel algorithm and its implementation structure...
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This paper presents a new generalized particle model (GPM) to generate the prediction coding for lossless data compression. Local rules for particle movement in GPM, parallel algorithm and its implementation structure to generate the desired predictive coding are discussed. The proposed GPM approach has advantages in terms of encoding speed, parallelism, scalability, simplicity, and easy hardware implementation over other sequential lossless compression methods
Maximum likelihood (ML) estimation is used during tomosynthesis mammography reconstruction. A single reconstruction involves the processing of high-resolution projection images, which is both compute-intensive and tim...
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Maximum likelihood (ML) estimation is used during tomosynthesis mammography reconstruction. A single reconstruction involves the processing of high-resolution projection images, which is both compute-intensive and time-consuming. This workload is presently a bottleneck in the accurate diagnosis of breast cancer during screening. This paper presents our parallelization work on an ML algorithm using three different partitioning models: no inter-communication, overlap with inter-communication and non-overlap model. These models are evaluated to obtain the best reconstruction performance given a range of computing environments with different computational power and network speed. Our test results show that the non-overlap method outperforms the other two methods on all five computing platforms evaluated. This parallelization of ML has enabled tomosynthesis to become a viable technology in the breast screening clinic, reducing reconstruction time from 3 hours on a PentiumIVworkstation to 6 minutes on a 32-node PentiumIV cluster
Many applications commonly found in digital signal processing and imageprocessing applications can be represented by data-flow graphs (DFGs). In our previous work, we proposed a new technique, extended retiming, whic...
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Many applications commonly found in digital signal processing and imageprocessing applications can be represented by data-flow graphs (DFGs). In our previous work, we proposed a new technique, extended retiming, which can be combined with minimal unfolding to transform a DFG into one which is rate-optimal. The result, however, is a DFG with split nodes, a concise representation for pipelined schedules. This model and the extraction of the pipelined schedule it represents have heretofore not been explored. In this paper, we develop new results regarding the construction of such graphs. We develop scheduling algorithms for such graphs, and then discuss a way to reduce the hardware requirements of such schedules. In the process, we state and prove a tight upper bound on the minimum number of processors required to execute the static schedule produced by our algorithms. We also construct an unfolding algorithm for split-node graphs and combine it with our scheduling methods to achieve rate-optimality in all cases. Finally, we demonstrate our methods on a specific example.
Spiral Architecture is a relatively new and powerful approach to general-purpose machine vision system. n this novel architecture, Spiral Addition and Multiplication achieve imageprocessing. As we all nown, fractal i...
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ISBN:
(纸本)1932415610
Spiral Architecture is a relatively new and powerful approach to general-purpose machine vision system. n this novel architecture, Spiral Addition and Multiplication achieve imageprocessing. As we all nown, fractal image compression methods have maximal image compression ratio, at the cost Of slow coding speed. This paper presents an algorithm to achieve high image compression ratio without slow coding speed on Spiral Architecture, which also improves the Spiral Architecture s usage in imageprocessing.
A review on the fractal image compression coding and the improvement measures are provided in this paper. The development process of the fractal image compression coding is introduced briefly. Some basic mathematic th...
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ISBN:
(纸本)9781932415582
A review on the fractal image compression coding and the improvement measures are provided in this paper. The development process of the fractal image compression coding is introduced briefly. Some basic mathematic theories about the fractal image compression coding are given. The main problems which exist in the fractal compression coding bring into focus. Some traditional and new methods about the fractal image compression coding are discussed. The advantages and disadvantages of these methods are comprehensively analy ed. And the mixture of these methods is concerned. It is believed that the fractal image compression coding will be one of the most effective methods in the field of digital image coding.
With the increasing importance of multiple multiplatform remote sensing missions, digital image registration has been applied into many fields, and specially plays a very important role in remotely sensed data process...
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ISBN:
(纸本)3540292357
With the increasing importance of multiple multiplatform remote sensing missions, digital image registration has been applied into many fields, and specially plays a very important role in remotely sensed data processing. Firstly a brief introduction of existing parallelmethods of wavelet-based global registration is given. And then the communication optimization for GP method is described. The optimized algorithm is named Group-Optimized-parallel (GOP for short). To find out the reason of occasionally lower efficiency of GOP than other methods, a more careful analysis is presented in theory and proved in experiments. Moreover, we give a quantitative criterion, called Remainder Items, to choose the best solution in different input conditions.
This paper presents a novel concept for resource management in cluster-based image retrieval systems. First, the paper describes image retrieval using static and dynamic feature extraction. The complexity of dynamic f...
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ISBN:
(纸本)9781932415582
This paper presents a novel concept for resource management in cluster-based image retrieval systems. First, the paper describes image retrieval using static and dynamic feature extraction. The complexity of dynamic feature extraction requires the utilization of powerful parallel architectures and in order to provide the user with reasonable response times. Most existing methods for resource management in parallelimage retrieval systems are based on sinlge query execution and do not take quality of service (QoS) aspects into account. This appears not to be practical in large-scale and commercial applications of image databases having a large number of users at any time. In order to allow an efficient utilization of the parallel system and to meet user-defined QoS demands associated with queries, we need to develop a new concept and a novel resource management architecture. Interesting aspects of the model include utility theory, flexible computations, QoS levels, and a hierarchical resource management architecture. Finally, an approach for algorithmic solution is described.
The proceedings contain 74 papers. The topics discussed include: web services composition for distributed data mining;how to run scientific applications over web services;resource management services for a grid analys...
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The proceedings contain 74 papers. The topics discussed include: web services composition for distributed data mining;how to run scientific applications over web services;resource management services for a grid analysis environment;a comparison of two methods for building astronomical image mosaics on a grid;gene sequence alignment on a public computing platform;parallel module network learning on distributed memory multiprocessors;a scalable parallel poisson solver in three dimensions with infinite-domain boundary conditions;factoring solution sets of polynomial systems in parallel;a programmable array processor architecture for flexible approximate string matching algorithms;and speculative parallel threading architecture and compilation.
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