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On the parallelization and Optimization of the Genetic-Based ANN Classifier for the Diagnosis of Students with Learning Disabilities

On the Parallelization and Optimization of the Genetic-Based...

引用

IEEE international conference on systems, Man and Cybernetics

作者： Wu, T-K Huang, S-C Lin, Y-L Chang, H. Meng, Y-R Natl Changhua Univ Educ Changhua Taiwan Natl Hsinchu Univ Educ Hsinchu Taiwan

ISBN: (纸本)9781424465880

Diagnosis of students with learning disabilities has long been a difficult issue as it requires extensive man power and takes a long time. Through genetic algorithm based feature selection method and genetic based parameters optimization, artificial neural network (ANN) classifier has proven to be a good predictor to the diagnosis of students with learning disabilities. In this study, we keep focusing on the ANN model and compare three strategies of parallelizing the ANN parameter optimization procedure with OpenMP and MPI APIs. Not surprisingly, the outcomes show that all three parameter optimization procedures indeed converged or executed more quickly with the aid of parallel processing. In particular, the genetic-based method tends to derive the best accuracy and require less execution time. Most important of all, potentially due to a more diverse search space provided by the distributed parallel processing environment, the accuracy of the genetic-based ANN classifier may also be improved in general. In addition, with appropriate combinations of features and parameters setting, the accuracy in LD identification model has exceeded the 90% mark (using 5-fold cross validation), which is the best we have achieved so far. The result suggests that genetic-based (or perhaps similar) optimization methods may be benefited, both in reducing execution time and achieving better outcome, from current grid-based computing technologies.

关键词： Learning Disabilities Genetic Algorithm Evolutionary Computation Grid computing Neural Network

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A parallel skeleton library for embedded multicores

A parallel skeleton library for embedded multicores

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international Workshop on Scheduling and Resource Management for parallel and distributed systems

作者： Liu, Xin Zhou, Jingyu Zhang, Daqiang Shen, Yao Guo, Minyi Department of Computer Science MOE-MS Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China

ISBN: (纸本)9780769541570

Many SoCs adopt multicore architectures. As a result, embedded programmers are also facing the challenge of parallel programming. We propose a parallel skeleton library that can be used on embedded multicores. Our library is implemented in standard C++ using template features. We propose two parallel skeletons to support common program patterns on multicores. In our skeleton library, programmers can easily choose underlying parallel implementations with no code changes. Experimental results show that many applications can take advantage of these two skeletons for performance improvement, sometimes better than hand-parallelized code. © 2010 IEEE.

关键词： C++ (programming language)

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A bi-criteria algorithm for scheduling parallel task graphs on clusters 10

A bi-criteria algorithm for scheduling parallel task graphs ...

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10th IEEE/ACM international Symposium on Cluster, Cloud, and Grid computing, CCGrid 2010

作者： Desprez, Frédéric Suter, Frédéric INRIA LIP ENS Lyon Lyon France IN2P3 Computing Center CNRS/IN2P3 Lyon-Villeurbanne France

ISBN: (纸本)9781424469871

Applications structured as parallel task graphs exhibit both data and task parallelism, and arise in many domains. Scheduling these applications on parallel platforms has been a long-standing challenge. In the case of a single homogeneous cluster, most of the existing algorithms focus on the reduction of the application completion time (makespan). But in presence of resource managers such as batch schedulers and due to accentuated pressure on energy concerns, the produced schedules also have to be efficient in terms of resource usage. In this paper we propose a novel bi-criteria algorithm, called biCPA, able to optimize these two performance metrics either simultaneously or separately. Using simulation over a wide range of experimental scenarios, we find that biCPA leads to better results than previously published algorithms. © 2010 IEEE.

关键词： Scheduling algorithms

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distributed approach for parallel exact critical path tracing fault simulation

Distributed approach for parallel exact critical path tracin...

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作者： Ivask, Eero Devadze, Sergei Ubar, Raimund Department of Computer Engineering Tallinn University of Technology Tallinn Estonia

ISBN: (纸本)9788392875635

distributed computing attempts to aggregate different computing resources available in enterprises and in the Internet for computation intensive applications in a transparent and scalable way. Fault simulation used in digital design flow for test quality evaluation can require a lot of processor and memory resources. To speed up simulation and to overcome the problem of memory limits in the case of very large circuits, a method of model partitioning and the procedure of parallel reasoning for several distributed simulation agents was proposed. The concept and implementation of web-based distributed system was introduced. © 2010 by Department of Microelectronics & Computer Science, Technical University of Lodz.

关键词： distributed computer systems

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paralleling clonal selection algorithm with OpenMP

Paralleling clonal selection algorithm with OpenMP

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international conference on Intelligent Network and Intelligent systems

作者： Zhu, Hongbing Chen, Sicheng Wu, Jianguo College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Dept. of Computer Science Faculty of Informatics Hiroshima Kokusai Gakuin University Hiroshima Japan College of Information Science and Engineering Wuhan University of Science and Technology Wuhan China

ISBN: (纸本)9780769542492

Clonal selection algorithm (CSA) is one of the most representative Immune algorithms (IA) and was applied into the protein structure prediction (PSP) on AB off-lattice model, but it required a long time in the calculation. So in this paper, a parallel clonal selection algorithm (CSA) was proposed, which was implemented using distributed computing model that employed OpenMP on four core computer. In the algorithm, several sub-populations replaced the original single population, and each sub-population evolved independently, and the current best individual was distributed into all the sub-populations. The parallel algorithm overcame premature convergence and found global optima efficiently. And the experiment results shown that the performance had been significantly improved. © 2010 Crown Copyright.

关键词： parallel algorithms

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Jedule: A tool for visualizing schedules of parallel applications

Jedule: A tool for visualizing schedules of parallel applica...

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international Workshop on Scheduling and Resource Management for parallel and distributed systems

作者： Hunold, Sascha Hoffmann, Ralf Suter, Frédéric International Computer Science Institute Berkeley CA United States Department of Computer Science University of Bayreuth Germany IN2P3 Computing Center CNRS/IN2P3 Lyon-Villeurbanne France

ISBN: (纸本)9780769541570

Task scheduling is one of the most prominent problems in the era of parallel computing. We find scheduling algorithms in every domain of computer science, e.g., mapping multiprocessor tasks to clusters, mapping jobs to grid resources, or mapping fine-grained tasks to cores of multicore processors. Many tools exist that help understand or debug an application by presenting visual representations of a certain program run, e.g., visualizations of MPI traces. However, often developers want to get a global and abstract view of their schedules first. In this paper we introduce Jedule, a tool dedicated to visualize schedules of parallel applications. We demonstrate the effectiveness of Jedule by showing how it helped analyzing problems in several case studies. © 2010 IEEE.

关键词： Mapping

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Towards personal high-performance geospatial computing (HPC-G): Perspectives and a case study

Towards personal high-performance geospatial computing (HPC-...

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18th ACM SIGSPATIAL international conference on Advances in Geographic Information System, ACM SIGSPATIAL HPDGIS 2010

作者： Zhang, Jianting Department of Computer Science City College of New York New York City NY 10031 United States

ISBN: (纸本)9781450304320

Cluster computing, Cloud computing and GPU computing play overlapping and complementary roles in parallel processing of geospatial data within the general HPC framework. The fast increasing hardware capacities of modern personal computers equipped with chip multiprocessor CPUs and massively parallel GPUs have made high performance computing of large-scale geospatial data in a personal computing environment possible. We discuss the framework of Personal HPC-G and compare it with traditional Cluster computing and the newly emerging Cloud computing. We consider Personal HPC-G possesses many favorable features: low initial and operational costs, good support for data management and excellent support for both numeric modeling and interactive visualization. A case study on developing a parallel spatial statistics module for visual explorations on top of Personal HPC-G is subsequently presented. Copyright 2010 ACM.

关键词： Cluster computing

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Proceedings - IEEE/IFIP international conference on Embedded and Ubiquitous computing, EUC 2010

Proceedings - IEEE/IFIP International Conference on Embedded...

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IEEE/IFIP 8th international conference on Embedded and Ubiquitous computing, EUC 2010

ISBN: (纸本)9780769543222

The proceedings contain 125 papers. The topics discussed include: schedule swapping: a technique for temperature management of distributed embedded systems;user-level network protocol stacks for automotive infotainment systems;replay debugging for multi-threaded embedded software;optimizing runtime reconfiguration decisions;architectural support for reducing parallel processing overhead in an embedded multiprocessor;trading conditional execution for more registers on ARM processors;co-simulation of self-adaptive automotive embedded systems;empirical evaluation of content-based pub/sub systems over cloud infrastructure;a reflective service gateway for integrating evolvable sensor-actuator networks with pervasive infrastructure;handling mobility on a QoS-aware service-based framework for mobile systems;trust measurement methods in organic computing systems by direct observation;and rule-based approach for context inconsistency management scheme in ubiquitous computing.

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Cloud computing: New challenge to the entire computer industry

Cloud computing: New challenge to the entire computer indust...

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2010 1st international conference on parallel, distributed and Grid computing, PDGC - 2010

作者： Mathur, Peeyush Nishchal, Nikhil Department of Computer Engineering Sobhasaria Engineering College Sikar India Sobhasaria Engineering College Sikar India

ISBN: (纸本)9781424476725

Cloud computing is a way of computing, via the Internet, that broadly shares computer resources instead of using software or storage on a local PC. Cloud computing is an outgrowth of the ease-of-access to remote computing sites provided by the Internet. Instead of installing a suite of software for each computer, we'd only have to load one application. That application would allow workers to log into a Web-based service which hosts all the programs the user would need for his or her job. Remote machines owned by another company would run everything from e-mail to word processing to complex data analysis programs. It's called cloud computing, and it could change the entire computer industry. In a cloud computing system, there's a significant workload shift. Local computers no longer have to do all the heavy lifting when it comes to running applications. The network of computers that make up the cloud handles them instead. Hardware and software demands on the user's side decrease. The only thing the user's computer needs to be able to run is the cloud computing systems interface software, which can be as simple as a Web browser, and the cloud's network takes care of the rest. © 2010 IEEE.

关键词： Cloud computing

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A high-performance scalable computing system on the RapidIO interconnect architecture

A high-performance scalable computing system on the RapidIO ...

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international conference on Cyber-Enabled distributed computing and Knowledge Discovery

作者： Zhang, Yong Wang, Yong Zhang, Ping Wireless Technology Innovation Institute Beijing University of Posts and Telecommunications Beijing 100876 China Key Laboratory of Universal Wireless Communication Ministry of Education Beijing University of Posts and Telecommunications Beijing 100876 China

ISBN: (纸本)9780769542355

In order to meet the demanding requirements of scalability, adaptability and computational capability of next-generation signal-processing system, a flexible and high-performance signal-processing module based on Serial RapidIO (SRIO) interconnect and Advanced Mezzanine Card (AMC) modules is developed. RapidIO is a packet-switched interconnect intended primarily as an intra-system interface, allowing chip-to-chip and board-to-board communications at 10 Gigabit per second performance levels. The AMC specification is defined by PCI Industrial Computer Manufacturer Group (PICMG) and mainly covers the base-level requirements for a wide-range of high-speed mezzanine cards optimized for, but not limited to, Advanced Telecommunications computing Architecture (ATCA) Carriers systems. With this versatile module, massively parallel multi-processor computing system is feasible. A prototype of 12 modules is introduced and an application of this computing system in MIMO-OFDM system is covered. © 2010 IEEE.

关键词： Packet switching

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