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RTOS support for parallel execution of hard real-time applications on the MERASA multi-core processor

RTOS support for parallel execution of hard real-time applic...

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13th IEEE international symposium on Object, Component, and Service-Oriented Real-Time distributed computing, ISORC 2010

作者： Wolf, Julian Gerdes, Mike Kluge, Florian Uhrig, Sascha Mische, Jörg Metzlaff, Stefan Rochange, Christine Cassé, Hugues Sainrat, Pascal Ungerer, theo University of Augsburg Germany University of Toulouse IRIT France

ISBN: (纸本)9780769540375

Multi-cores are the contemporary solution to satisfy high performance and low energy demands in general and embedded computing domains. However, currently available multi-cores are not feasible to be used in safety-critical environments with hard real-time constraints. Hard real-time tasks running on different cores must be executed in isolation or their interferences must be time-bounded. thus, new requirements also arise for a real-time operating system (RTOS), in particular if the parallel execution of hard real-time applications should be supported. In this paper we focus on the MERASA1 system software as an RTOS developed on top of the MERASA multi-core processor. the MERASA system software fulfils the requirements for time-bounded execution of parallel hard real-time tasks. In particular we focus on thread control with synchronisation mechanisms, memory management and resource management requirements. Our evaluations show that all system software functions are time-bounded by a worst-case execution time (WCET) analysis. © 2010 IEEE.

关键词： parallel processing systems

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A new development of public key cryptosystem

A new development of public key cryptosystem

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2010 7th international symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2010

作者： Yang, Xiao Bo Boussakta, Said Al-Gailani, Mohammed School of Electrical Electronic and Computing Engineering Newcastle University Newcastle Upon Tyne NE1 7RU United Kingdom

ISBN: (纸本)9781861353696

A public-key encryption algorithm and a practical hybrid scheme are proposed in this paper. this algorithm uses the advanced transform techniques, i.e. the Number theoretic Transforms (NTTs) to diffuse data, and uses a non-linear technique based on the Elliptic Curve Discrete Logarithm Problem (ECDLP) to confuse data. the main advantage of the proposed algorithm is its high efficiency and capability. the plaintext can be encrypted in blocks in parallel, thus saves computational time. the proposed algorithm also can be easily applied in a hybrid scheme for practical applications. © 2010 IEEE.

关键词： Mathematical transformations

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Design and implementation of parallel JiST to support distributed wireless network simulation

Design and implementation of parallel JiST to support distri...

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7th international symposium on High-Capacity Optical Networks and Enabling Technologies, HONET 2010

作者： Slavik, Michael Mahgoub, Imad Badi, Ahmed Ilyas, Mohammad Department of Computer Science and Engineering Florida Atlantic University Boca Raton FL United States

ISBN: (纸本)9781424499243

JiST/SWANS is a wireless network simulator gaining increasing popularity for ad-hoc wireless, wireless sensor network, and vehicular network evaluations. Typical published results using this tool show node counts on the order of hundreds of nodes. However, realistic sensor and vehicular networks may contain many more nodes than that. One reason for this discrepancy is the computational cost of evaluation via simulation. Currently, cluster computers are becoming preferred over expensive multi-processor supercomputers for improving computational output. We present the design and implementation of a parallelization of JiST, the discrete event simulator core of JiST/SWANS. JiST uses unique dynamic byte-code rewriting to simplify the development of applications and has been shown to perform well running small- or medium-scale wireless network simulations on single processor systems. We propose an optimistic cluster-based architecture and apply it to JiST. Simulation entity memory is distributed evenly across all nodes in the cluster, resulting in linear memory growth. Details of the simulation engine including the complex event execution synchronization are hidden entirely from the application, easing development and debug time. Since JiST is the simulation backend of the SWANS wireless network simulator, this result is the first step in simulating large networks using SWANS in reasonable periods of time. Results presented show the performance of our parallelization of JiST is in line with the performance of other existing parallel discrete event simulators. © 2010 IEEE.

关键词： Supercomputers

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parallelization Strategies for computing PageRank

Parallelization Strategies for Computing PageRank

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7th international Conference on Engineering Computational Technology

作者： Migallon, H. Migallon, V. Palomino, J. A. Penades, J. Univ Miguel Hernandez Dept Phys & Comp Architectures Alicante Spain Univ Alicante Dept Comp Sci & Artificial Intelligence Alicante Spain

ISBN: (纸本)9781905088416

the PageRank algorithm for determining the importance of Web pages has become a central technique in Web search. this algorithm uses the Power method to compute successive iterates that converge to the principal eigenvector of the Markov chain representing the Web link graph. In this paper different parallel implementations of the PageRank algorithm are proposed. Synchronous and asynchronous implementations of the Power method are analyzed using different data distribution strategies. the algorithms described here have been implemented on two parallel computers. the first platform is a DELL PowerEdge 2900 with two Quad-Core Intel Xeon 5320 sequence processors at up to 1.86 GHz. the second platform is a Beowulf cluster of 6 nodes Intel x86 connected through a 1 Gb/sec. Each node consists of two Intel Xeon Quad-Core processors at up to 2.60 GHz with 8 GB of RAM. the reported experiments show the behaviour of the designed algorithms for realistic test data on both shared and distributed architectures.

关键词： PageRank parallel algorithms Power method shared memory distributed memory sychronous and asynchronous iterations

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A load balancing skyline query algorithm in high bandwidth distributed systems

A load balancing skyline query algorithm in high bandwidth d...

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2010 7th international Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2010

作者： Huang, Jin Chen, Jian Du, Qing Yin, Jian School of Information Science and Technology Sun Yat-sen University South China Normal University Guangzhou 510275 China School of Software Engineering South China University of Technology Guangzhou 510006 China School of Information Science and Technology Sun Yat-sen University Guangzhou 510275 China

ISBN: (纸本)9781424459346

Skyline queries, which retrieve the points that are not dominated by any other points in a given dataset, are well recognized as a powerful tool in multi-criteria decision making. Most of the previous works focus on computing skylines on centralized environments typically with one CPU. In this paper, to scale up skyline computation on large datasets, we propose a load balancing parallel skyline query algorithm for multi-processor clusters or high-speed network environments. Our algorithm utilizes the monotonic ordering and clustering properties of Z-order to reduce dominance tests and significantly shortens the response time by performing parallel processing over multiple processors. Our algorithm is progressive, fast convergent and scalable. Extensive experiments were conducted to demonstrate the feasibility and effectiveness of the proposed algorithm. ©2010 IEEE.

关键词： HIgh speed networks

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Dynamic task scheduling using fuzzy logic in distributed memory systems

Dynamic task scheduling using fuzzy logic in distributed mem...

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2010 7th international Conference on Informatics and Systems, INFOS2010

作者： Omara, Fatma A. Zohier, Rasha M. Computer Science Department Faculty of Computer and Information Cairo University Egypt Computer Science Department Institute of Statistical Studies and Research Cairo University Egypt

ISBN: (纸本)9789774033964

the scheduling and mapping of the precedence-constrained task graphs of parallel programs to processors is considered one of the most crucial NP-complete problems in parallel and distributed computing systems. In this paper, a dynamic task scheduling model based on fuzzy logic is proposed. the main objective of this technique is to improve the fuzzy decision which is used in task scheduling on a network of processing elements by introducing new input parameters to an existing fuzzy model and, in the same time, improving the load balance on the network in a dynamic environment. the proposed Fuzzy Model is capable of processing inputs from on the fly data that arises from the current state of the processors. According to the proposed model, tasks are generated randomly and are served based on the First-Come-First-Serve rule. When the task is ready to be assigned, its information is passed to the processors for bidding. Each processor has a local scheduler for managing its own activities, which supplies information on its current state and follows whatever decision is given where the fuzzy logic mechanism is used in making decision on the task assignment. A comparative study between the existed fuzzy model and our modified fuzzy model has been done. the comparative results show that our modified fuzzy model outperforms the existed one.

关键词： Fuzzy logic

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Agent Swarm Optimization: A Platform to Solve Complex Optimization Problems

Agent Swarm Optimization: A Platform to Solve Complex Optimi...

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7th international Conference on Engineering Computational Technology

作者： Montalvo, I. Izquierdo, J. Herrera, M. Perez, R. Univ Politecn Valencia Dept Hydraul Engn & Environm E-46022 Valencia Spain

ISBN: (纸本)9781905088416

Agent Swarm Optimization (ASO) is a newly introduced abstract term to refer to a class of extensible algorithms devoted to solve complex optimization problems where classical techniques and most recent evolutionary algorithms get stranded. ASO stands for Agents Swarms Optimization. ASO is based on a multi-agent philosophy that crystallizes on a platform where different kinds of agents may interact and co-operate in the solution of a given optimization problem. In ASO such different evolutionary algorithms as PSO, ACO, GA, etc. may coexist contributing with their own agents, which are endowed with their specific characteristics, to the collective solution of the same problem. Taking advantage of parallel and distributed computation, allowing real-time enrolment of new agents, and raising the possibility for a human (the user) to become an active agent in the solution process make ASO a first-rate option to solve important decision-making problems in engineering, including the consideration of either one or multiple objectives. In this paper we present an ASO application developed for the optimal design of water distribution systems. In this specific problem, where the main objective is the sizing of the network elements, it can be seen that the introduction of a set of problem-specific rules regarding the agents' behaviours, considerably favours the search of solutions. the work includes solutions for two real-world water distribution networks where the role of ASO clearly improves the quality of the performed multiobjective optimization. the synergic co-operation between agents of different species and the use of general search algorithms based on parallel and distributed computation open up new possibilities to face complex engineering problems, as shown in this work.

关键词： water supply networks optimal design multiobjective optimization swarm intelligence parallel computing distributed computing

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Service-Oriented Volunteer computing for Massively parallel Constraint Solving Using Portfolios

Service-Oriented Volunteer Computing for Massively Parallel ...

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7th international Conference Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems

作者： Kiziltan, Zeynep Mauro, Jacopo Univ Bologna Dept Comp Sci I-40126 Bologna Italy

ISBN: (纸本)9783642135194

Recent years have witnessed growing interest in parallelising constraint solving based on tree search (see [1] for a brief overview). One approach is search-space splitting in which different parts of the tree are explored in parallel (e.g. [2]). Another approach is the use of algorithm portfolios. this technique exploits the significant variety in performance observed between different algorithms and combines them in a portfolio [3]. In constraint solving, an algorithm can be a solver or a tuning of a solver. Portfolios have often been run in an interleaving fashion (e.g. [4]). their use in a parallel context is more recent ([5], [1]). © 2010 Springer-Verlag.

关键词： distributed computer systems

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Automatic Tuning of MPI Runtime Parameter Settings by Using Machine Learning 10

Automatic Tuning of MPI Runtime Parameter Settings by Using ...

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7th ACM international Conference on computing Frontiers (CF)

作者： Pellegrini, Simone Fahringer, thomas Jordan, Herbert Moritsch, Hans Univ Innsbruck Distributed & Parallel Syst Grp Technikerstr 21A A-6020 Innsbruck Austria

ISBN: (纸本)9781450300445

MPI implementations provide several hundred runtime parameters that can be tuned for performance improvement. the ideal parameter setting does not only depend on the target multiprocessor architecture but also on the application, its problem and communicator size. this paper presents ATune, an automatic performance tuning tool that uses machine learning techniques to determine the program-specific optimal settings for a subset of the Open MPI's runtime parameters. ATune learns the behaviour of a target system by means of a training phase where several MPI benchmarks and MPI applications are run on a target architecture for varying problem and communicator sizes. For new input programs, only one run is required in order for ATune to deliver a prediction of the optimal runtime parameters values. Experiments based on the NAS parallel Benchmarks performed on a cluster of SMP machines are shown that demonstrate the effectiveness of ATune. For these experiments, ATune derives MPI runtime parameter settings that are on average within 4% of the maximum performance achievable on the target system resulting in a performance gain of up to 18% with respect to the default parameter setting.

关键词： MPI runtime parameters tuning machine learning

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Spatial Enrichment by Applying Hierarchy to Built Infrastructure

Spatial Enrichment by Applying Hierarchy to Built Infrastruc...

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7th international Conference on Engineering Computational Technology

作者： Varduhn, V. Frisch, J. Mundani, R. -P. Rank, E. Tech Univ Munich Computat Engn D-80290 Munich Germany

ISBN: (纸本)9781905088416

this paper shows how hierarchical organisation of data from construction and built infrastructure can help to overcome limitations of nowadays systems that arise from distributed storing and different file formats. this hierarchy, once established, can then be used to ensure fast access to vast amounts of distributed data and enriches the information basis by spatial context, such that information spread over former distinct storage locations are connected to each other and therefore can be treated in a combined and unified fashion. Since in our approach an octree structure is used to hold the spatial assembly of the models, many properties such as intersection detection of objects or voxel representations can be evaluated efficiently, to still have access to the original geometry if necessary - each voxel of the octree stores an additional link to the respective CAD entity.

关键词： spatial augmentation built infrastructure (BIM/IFC) hierarchical data structures computational steering parallel computing visibility analysis proximity analysis

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