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检索条件"任意字段=9th International Conference on Parallel and Distributed Computing, Applications and Technologies"

共 1770 条记录，以下是881-890 订阅

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Enhancing Traditional Games with Augmented Reality technologies

Enhancing Traditional Games with Augmented Reality Technolog...

引用

IEEE 9th international conference on Ubiquitous Intelligence and computing (UIC) / IEEE 9th international conference on Autonomic and Trusted computing (ATC)

作者： Sakuma, Hiroyuki Yamabe, Tetsuo Nakajima, Tatsuo Waseda Univ Dept Comp Sci & Engn Tokyo Japan

ISBN: (纸本)9780769548432

Digital technologies are useful to enhance existing traditional games to increase their pleasure. In many games, digital technologies can add special effects to excite a player emotionally. However, the technologies are also useful to help a player to learn complex rules in the games. Especially, traditional games like a poker are not easy to learn for beginners so many recent young people lose interests to play the games. In this paper, we present AR-Hold'em that is an enhanced Texas Hold'em poker game with augmented reality technologies. We also present some user studies showing the effectiveness of our approach.

关键词： Augmented Reality Card Games

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Preliminary Search Engine for Open Protein Identification

Preliminary Search Engine for Open Protein Identification

引用

13th international conference on parallel and distributed computing, applications, and technologies (PDCAT)

作者： Zhang, Wenli Chi, Hao Lu, Yuanzheng Huang, Yuqing Zhao, Xiaofang He, Simin Chinese Acad Sci Inst Comp Technol Beijing Peoples R China

ISBN: (纸本)9780769548791

Protein identification is the most important and basic problem for proteomics. Using tandem mass spectrometry and database search is one of the most widely used identification techniques. However, the improved sensitivity of mass spectrometers, rapid expansion of databases and more complex analysis, like post-translational modification and non-specific enzymatic digestion, have challenged current restricted protein identification search engines in scale and speed severely. In this paper, we proposed an open protein identification method relaxing enzyme, and presented our distributed design to support big protein database with non-specific digestion analysis based on pFind, a practical tandem mass spectra search engine developed in China. With classical bigger protein databases *** and uniprot-sprot we got nearly linear speedup in a 20-blade cluster. By further analysis, we can expect real time identification to some extent.

关键词： open protein identification non-specific enzymatic digestion search engine distributed cluster

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A Test Generation Method Based on Model Reduction for parallel Software

A Test Generation Method Based on Model Reduction for Parall...

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13th international conference on parallel and distributed computing, applications, and technologies (PDCAT)

作者： Sun, Tao Ye, Xinming Liu, Jing Inner Mongolia Univ Coll Comp Sci Hohhot Peoples R China

ISBN: (纸本)9780769548791

Modeling and testing for parallel software systems is difficult, because the number of states and execution fragments expand significantly caused by parallel behaviors, so that many traditional testing methods cannot work effectively for this kind of software. In this paper, a test sequence generation method based on model reduction for parallel software systems is shown. Firstly, a formal model for software system specification is constructed based on Coloured Petri Net (CPN), called system model;and a model reduction method based on trace-equivalent principle is shown and applied on system model, which could generate an external behavior equivalent model with smaller scale. Secondly, a linear behavior sequence of the system is specified using CPN, called LBS model, which represents testing purpose in a test case, and some operations between state space diagrams of system model and LBS model are defined, so that a sub-graph of system model state space diagram is generated, which could cover all executions of system model that involves behaviors of LBS. Finally, a performance analysis shows the effectiveness of the method.

关键词： test generation reduction Coloured Petri Net

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LPFSC: A Light Weight parallel Framework for Super computing

LPFSC: A Light Weight Parallel Framework for Super Computing

引用

13th international conference on parallel and distributed computing, applications, and technologies (PDCAT)

作者： Ou, Yulong Li, Bo Yuan, Zheng Hao, Qiang Luan, Zhongzhi Qian, Depei Beihang Univ Sino German Joint Software Inst Dept Comp Sci & Engn Beijing 100191 Peoples R China

ISBN: (纸本)9780769548791

Supercomputing on the heterogeneous architectures that integrate multi-core or many-cores processors has been developed at a dramatically speed. It is widely used in theoretical physics, theoretical chemistry, climate modeling, biology simulation and medicine research for high-performance and energy-efficient computing. Yet it is still a big challenge to users when trying to run their scientific applications efficiently on large-scale supercomputers constructed by using heterogeneous multiprocessors. On the other hand, overhead cost issues of a large supercomputer for its resource managements, job scheduling, and system reliability become more and more important. In this paper, LPFSC, a light weight parallel framework for supercomputing, is presented, which helps programmers in planning their tasks on a supercomputer. In a huge supercomputer system, there might be a hundred of thousands of nodes, over a million processor cores and many other kinds of processors, general main-slave computing mode can hardly handle the huge amount of heterogeneous processors. LPFSC consists of modules for multiple master-slave support, load balance among huge amount computing tasks, and reliability support. Additional features will be added in the near future and it is supposed to provide good support for large heterogeneous computer systems. Finally, large amount tasks of 2D-FFT in varying size are tested under the framework for evaluation, which can scale to more than 300 processors.

关键词： LPSFC heterogeneous architecture supercomputing

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Scaling the distributed Stochastic Simulation to Exaflop Supercomputers

Scaling the Distributed Stochastic Simulation to Exaflop Sup...

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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： Glinsky, Boris Rodionov, Alexei Marchenko, Mikhail Podkorytov, Dmitry Weins, Dmitry Inst Computat Math & Math Geophys SB RAS Lab Siberian Supercomp Ctr Lab Dynam Proc Simulat Informat Networks Lab Monte Carlo Methods Novosibirsk Russia

ISBN: (纸本)9780769547497

the Monte-Carlo method (stochastic simulation) is the one of the major tools in statistical physics, complex systems science and many other fields and is considered to be the promising computational scheme to run on nearest future exaflop supercomputers with many thousands and even millions of computational cores. We suggest a technique of the distributed stochastic simulation suitable for running on large amount of computational cores of the supercomputer. An example of the highly scalable application utilizing distributed stochastic simulation on up-to-date tera- and petaflop supercomputers is the program library PARMONC. thorough examination of the proposed technique was done using simulation model that is based on the multiagent simulation system AGNES. the AGNES in particular enables one to evaluate the performance of the supposed exaflop supercomputer loaded with the distributed stochastic simulation.

关键词： Multiagent systems simulation parallel architectures supercomputers Monte Carlo methods parallel algorithms distributed computing random number generation

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Stratus: A distributed computing framework for scientific simulations on the cloud

Stratus: A distributed computing framework for scientific si...

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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： Jakovits, Pelle Srirama, Satish Narayana Kromonov, Ilja Univ Tartu Inst Comp Sci Tartu Estonia

ISBN: (纸本)9780769547497

Cloud is a promising source for computing resources when solving scientific problems. Several large companies have entered the cloud computing market in recent times and are providing cloud computing services like Infrastructure as a Service (IaaS) that provide virtual computer machines on demand. these virtual machines can easily be used for the high performance computing needs by applying distributed computing methods and frameworks. the SciCloud project at the University of Tartu has studied adapting scientific computing algorithms to different distributed computing frameworks like MapReduce and its optimizations. the study has concluded that the current solutions do not fully support complex iterative algorithms, which are commonly used in scientific simulations. this paper presents a design for a new distributed computing framework, Stratus, which fully supports scientific computing algorithms and takes advantage of the characteristics that have made cloud such a convenient and popular source for computing resources. the paper also describes the motivation for creating a brand new solution, outlines its architecture and design, and gives an overview on how algorithms can be adapted to this framework.

关键词： Cloud computing Bulk Synchronous parallel distributed computing Scientific computing MapReduce

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Lung Cancer Detection in Chest X-Ray Images with parallel Genetic Algorithm

Lung Cancer Detection in Chest X-Ray Images with Parallel Ge...

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13th international conference on parallel and distributed computing, applications, and technologies (PDCAT)

作者： Peng Gang Liu Li Zeng Kehan Li Tian Nakayama, Shigeru Huizhou Univ Dept Comp Sci & Technol Huizhou City 516007 Guangdong Peoples R China Kagoshima Univ Dept Informat Sci & Biomed Engn Kagoshima Japan

this paper discusses lung cancer detection in chest X-ray images with a parallel genetic algorithm (GA). the template matching method and local search techniques are combined to the algorithm and JavaSpaces is used to... 详细信息

ISBN: (纸本)9780769548791

关键词： lung cancer chest X-ray image genetic algorithm parallel system

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Accelerating Computation of DCM for ERP with GPU-Based parallel Strategy

Accelerating Computation of DCM for ERP with GPU-Based Paral...

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IEEE 9th international conference on Ubiquitous Intelligence and computing (UIC) / IEEE 9th international conference on Autonomic and Trusted computing (ATC)

作者： Wang, Wei-Jen Hsieh, I-Fan Chen, Chun-Chuan Natl Cent Univ Dept Comp Sci & Informat Engn Tao Yuan 320 Taiwan Natl Cent Univ Grad Inst Biomed Engn Tao Yuan 320 Taiwan

ISBN: (纸本)9780769548432;9781467330848

this paper presents the use of graphic processing unit (GPU) to accelerate a brain-activity analytical tool, the Dynamic Causal Modelling for Event Related Potential (DCM for ERP) in MATLAB. DCM for ERP is a recently developed advanced method for studying neuronal effective connectivity and making inference about the brain functions. DCM utilizes an iterative procedure, the expectation maximization (EM) algorithm, to find the optimal parameters given a set of observed events (data) and the underlying probability model, such that the likelihood function is maximized. As the EM algorithm is computationally demanding, time consuming and largely data dependent, we propose a parallel computing scheme using GPUs to achieve a fast estimation of neural effective connectivity in DCM. the computational loading of EM was partitioned and dynamically distributed to either the threads or blocks according to the DCM model complex (i.e. the number of parameters to be estimated). the performance of this dynamic loading arrangement in terms of execution time and accuracy loss were evaluated using synthetic data. the results show that our method can accelerate a computation task by about 30 times as fast as the MATLAB version.

关键词： Dynamic causal modelling expectation maximization CUDA parallel computing

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Garbage Collection for Service Oriented distributed Reliable Environment D-ReServE

Garbage Collection for Service Oriented Distributed Reliable...

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13th international conference on parallel and distributed computing, applications, and technologies (PDCAT)

作者： Brzezinski, Jerzy Danilecki, Arkadiusz Holenko, Mateusz Kobusinska, Anna Zierhoffer, Piotr Poznan Univ Tech Inst Comp Sci Poznan Poland

ISBN: (纸本)9780769548791

D-ReServE increases reliability of SOA-based systems in case of failure occurrence. the fault-tolerant information in D-ReServE is stored in the Stable Storage, which available space depletes with time. thus, in this paper we propose a garbage collection protocol for D-ReServE that allows the periodic purging of the Stable Storage, and discuss the challenges of garbage collection due to the nature of SOA systems.

关键词： SOA fault tolerance reliability rollback-recovery garbage-collection

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Revisiting Snapshot Algorithms by Refinement-based Techniques

Revisiting Snapshot Algorithms by Refinement-based Technique...

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13th international conference on parallel and distributed computing, applications, and technologies (PDCAT)

作者： Andriamiarina, Manamiary Bruno Mery, Dominique Singh, Neeraj Kumar Univ Lorraine LORIA Vandoeuvre Les Nancy France Univ York York N Yorkshire England

ISBN: (纸本)9780769548791

the snapshot problem addresses a collection of important algorithmic issues related to the distributed computations, which are used for debugging or recovering the distributed programs. Among the existing solutions, Chandy and Lamport propose a simple distributed algorithm. In this paper, we explore the correct-by-construction process to formalize the snapshot algorithms in distributed system. the formalization process is based on a modeling language Event B, which supports a refinement-based incremental development using RODIN platform. these refinement-based techniques help to derive a correct distributed algorithm. Moreover, we demonstrate how this class of other distributed algorithms can be revisited. A consequence is to provide a fully mechanized proof of the distributed algorithms.

关键词： distributed algorithms correctness by construction snapshot verification

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