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检索条件"任意字段=10th International Conference on Parallel and Distributed Computing, Applications and Technologies"

共 1765 条记录，以下是551-560 订阅

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Asynchronous Remote Communities (ARC) for researching distributed populations 10

Asynchronous Remote Communities (ARC) for researching distri...

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10th EAI international conference on Pervasive computing technologies for Healthcare, PervasiveHealth 2016

作者： MacLeod, Haley Jelen, Ben Prabhakar, Annu Oehlberg, Lora Siek, Katie Connelly, Kay Indiana University United States University of Calgary Canada

ISBN: (纸本)9781631900501

Existing research methods are largely intended to be conducted colocated and synchronously with a study population, but this approach is not feasible with remote or distributed populations. We describe a needs assessment study we conducted on Facebook. We report on our use of adapted versions of commonly used HCI research methods and lessons learned from this approach. © 2016 EAI.

关键词： Social networking (online)

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parallel implementation of searching the most similar subsequence in time series for computer systems with distributed memory 10

Parallel implementation of searching the most similar subseq...

引用

10th Annual international Scientific conference on parallel computing technologies, PCT 2016

作者： Movchan, A.V. Zymbler, M.L. South Ural State University Chelyabinsk Russia

the paper presents parallel implementation of searching the most similar subsequence in time series for computer cluster system with nodes based on Intel MIC accelerators. the algorithm involves three levels of data parallelism. the first level provides partitioning of time series into equal-length fragments, each of which is processed on a separate node of the computer cluster;nodes interact using MPI technology. the second level of parallelism supposes division of the fragment into equal-length segments and processing of each segment by a separate thread by means of OpenMP technology. the third level provides load balancing between CPU and accelerator. CPU performs pruning of dissimilar subsequences. Accelerator performs heavy-weighted calculations of similarity measure. the results of experiments confirm the efficiency of algorithm.

关键词： Time series

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Estimate of locality of parallel algorithms implemented on GPUs 10

Estimate of locality of parallel algorithms implemented on G...

引用

10th Annual international Scientific conference on parallel computing technologies, PCT 2016

作者： Likhoded, N.A. Paliashchuk, M.A. Belarusian State University Belarus

the problem of obtaining blocks of operations and threads of parallel algorithm resulting in a smaller number of accesses to global memory and resulting in the efficient use of caches and shared memory graphics processor is investigated. We formulated and proved statements to assess the volume of communication transactions generated by alternative sizing of blocks, as well as to minimize the number of cache misses due to the use of temporal and spatial locality of data. the research is constructive and allows software implementation for practical use.

关键词： parallel algorithms

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QoS-aware scheduling of Workflows in Cloud computing environments 30

QoS-aware scheduling of Workflows in Cloud Computing environ...

引用

30th IEEE international conference on Advanced Information Networking and applications (IEEE AINA)

作者： Bousselmi, Khadija Brahmi, Zaki Gammoudi, Mohamed Mohsen Fac Sci Tunis Tunis Tunisia Univ Sousse ISITCOM Sousse Tunisia Univ Mannouba ISAMM Mannouba Tunisia

ISBN: (纸本)9781509018574

Cloud computing has emerged as a service model that enables on-demand network access to a large number of available virtualized resources and applications with a minimal management effort and a minor price. the spread of Cloud computing technologies allowed dealing with complex applications such as Scientific Workflows, which consists of a set of intensive computational and data manipulation operations. Cloud computing helps such Workflows to dynamically provision compute and storage resources necessary for the execution of its tasks thanks to the elasticity asset of these resources. However, the dynamic nature of the Cloud incurs new challenges, as some allocated resources may be overloaded or out of access during the execution of the Workflow. Moreover, for data intensive tasks, the allocation strategy should consider the data placement constraints since data transmission time can increase notably in this case which implicates the increase of the overall completion time and cost of the Workflow. Likewise, for intensive computational tasks, the allocation strategy should consider the type of the allocated virtual machines, more specifically its CPU, memory and network capacities. Yet, a critical challenge is how to efficiently schedule the Workflow tasks on Cloud resources to optimize its overall quality of service. In this paper, we propose a QoS-aware algorithm for Scientific Workflows scheduling that aims to improve the overall quality of service (QoS) by considering the metrics of execution time, data transmission time, cost, resources availability and data placement constraints. We extended the parallel Cat Swarm Optimization (PCSO) algorithm to implement our proposed approach. We tested our algorithm within two sample Workflows of different scales and we compared the results to those given by the standard PSO, the CSO and the PCSO algorithms. the results show that our proposed algorithm improves the overall quality of service of the tested Workflows.

关键词： Cloud computing Workflow IaaS virtual machine storage quality of service scheduling algorithm parallel Cat Swarm Optimization

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Implementation of a parallel algorithm for searching the global extremum of a function on Intel Xeon Phi 10

Implementation of a parallel algorithm for searching the glo...

引用

10th Annual international Scientific conference on parallel computing technologies, PCT 2016

作者： Barkalov, K.A. Lebedev, I.G. Sovrasov, V.V. Sysoyev, A.V. Lobachevsky State University of Nizhni Novgorod Russia

the paper considers parallel algorithm for solving multiextremal optimization problems. the issues of implementation of the algorithm on state-of-the-art computing systems using Intel Xeon Phi coprocessor are examined. Two approaches for algorithm parallelization, which take into account information about laboriousness of the objective function computing, are considered. Speed up of the algorithm using Xeon Phi compared to the algorithm using CPU only is experimentally confirmed. Computational experiments are carried out on Lobachevsky supercomputer.

关键词： Global optimization

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parallel high performance graph processing 10

Parallel high performance graph processing

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10th Annual international Scientific conference on parallel computing technologies, PCT 2016

作者： Chernoskutov, M.A. Institute of Mathematics and Mechanics UB RAS Russia Ural Federal University Russia

Paper describes methods devoted to drastically speedup parallel breadth-first search algorithm. Main obstacle on the way to effectively parallelize breadth-first search is workload imbalance within computing nodes as well as significant volume of transferred data in the end of every iteration of the algorithm. Two methods are suggested in this paper to overcome these challenges. First method allows to distribute workloads between OpenMP threads in single node. Second method allows to reduce data transfer volume by using the hybrid graph traversal.

关键词： Data transfer

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Grand challenge: Graph CEP - Real-time data analytics using parallel complex event and graph processing 10

Grand challenge: Graph CEP - Real-time data analytics using ...

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10th ACM international conference on distributed and Event-Based Systems, DEBS 2016

作者： Mayer, Ruben Mayer, Christian Tariq, Muhammad Adnan Rothermel, Kurt IPVS University of Stuttgart Germany

ISBN: (纸本)9781450340212

In recent years, the proliferation of highly dynamic graphstructured data streams fueled the demand for real-time data analytics. For instance, detecting recent trends in social networks enables new applications in areas such as disaster detection, business analytics or health-care. parallel Complex Event Processing has evolved as the paradigm of choice to analyze data streams in a timely manner, where the incoming data streams are split and processed independently by parallel operator instances. However, the degree of parallelism is limited by the feasibility of splitting the data streams into independent parts such that correctness of event processing is still ensured. In this paper, we overcome this limitation for graph-structured data by further parallelizing individual operator instances using modern graph processing systems. these systems partition the graph data and execute graph algorithms in a highly parallel fashion, for instance using cloud resources. To this end, we propose a novel graph-based Complex Event Processing system GraphCEP and evaluate its performance in the setting of two case studies from the DEBS Grand Challenge 2016. © 2016 ACM.

关键词： Graphic methods

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the R2-D2 Toolchain - Automated Porting of Safety-Critical applications to FPGAs

The R2-D2 Toolchain - Automated Porting of Safety-Critical A...

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international conference on Reconfigurable computing and FPGAs (ReConFig)

作者： Vaas, Steffen Reichenbach, Marc Margull, Ulrich Fey, Dietmar Friedrich Alexander Univ Erlangen Nurnberg FAU Chair Comp Architecture Martensstr 3 D-91058 Erlangen Germany Tech Hsch Ingolstadt Esplanade 10 D-85049 Ingolstadt Germany

ISBN: (纸本)9781509037070

Safety-critical applications require reliable hardware platforms with deterministic behavior. Concerning the increasing demand for performance, current single core solutions are not sufficient anymore. Classical multi-core processors are designed for a general application case, which provide much performance at the expense of determinism and reliability. In safety-critical applications, all required tasks are already known at development time. they are specified by a system description, like AUTOSAR. thus, a hardware architecture providing one core for each task and one physical link for each data exchange between different tasks can be derived. However, such a highly application-specific architecture is not available. Latest FPGA technologies provide now enough resources to integrate several soft-core processors in one low-cost chip. Furthermore, the cores and their connections can be arranged flexibly in an FPGA. To bridge the gap between safety-critical applications and FPGAs, this approach provides a toolchain as addition to existing AUTOSAR design tools for automatically generating a specific hardware architecture from metadata of an AUTOSAR description. By reducing the complexity of the hardware platform drastically, a reconfigurable, reliable, deterministic, distributed ((R2-D2) hardware architecture can be created. the results show that safety-critical tasks can be executed deterministically on one chip in parallel and multiple applications can be mapped to one low-cost FPGA. Furthermore, the latency of the system could be reduced extensively, so new application areas can be accessed.

关键词： Real-Time Many-Core Decentralized Safety-Critical Automotive Reconfigurable Reliable Deterministic distributed NoC

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parallel and distributed computing, applications and technologies, PDCAT Proceedings

Parallel and Distributed Computing, Applications and Technol...

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17th international conference on parallel and distributed computing, applications and technologies, PDCAT 2016

ISBN: (纸本)9781509050819

the proceedings contain 74 papers. the topics discussed include: runahead cache misses using bloom filter;performance and portability studies with OpenACC accelerated version of GTC-P;outer-loop auto-vectorization for SIMD architectures based on open64 compiler;on routing of multiple concurrent user requests in multi-radio multi-channel wireless mesh networks;managing broadband access network with a SDN-based system;efficient scheduling strategy for mobile charger in wireless rechargeable sensor networks;efficient data retrieval algorithm for multi-request in multi-antenna wireless networks;accurate evaluation of bivariate polynomials;bilateral sampling randomized singular value decomposition;mePaaS: mobile-embedded platform as a service for distributing fog computing to edge nodes;a survey of challenging issues and approaches in mobile cloud computing;energy efficient scheduling of real time tasks on large systems;energy aware scheduling on heterogeneous multiprocessors with DVFS and duplication;green-aware online resource allocation for geo-distributed cloud data centers on multi-source energy;optimal scheduling algorithm of MapReduce tasks based on QoS in the hybrid cloud;towards an efficient maintenance of address space overflow for array based storage system;making user-level VMM for deterministic parallelism nonblocking and efficient;depth feature based accurate saliency detection for 3D images;and a variable Markovian based outlier detection method for multi-dimensional sequence over data stream.

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GPGPU based Concurrent Classification using Trained Model of Handwritten Digits

GPGPU based Concurrent Classification using Trained Model of...

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10th international conference on Open Source Systems and technologies (ICOSST)

作者： Rizvi, Syed Tahir Hussain Cabodi, Gianpiero Arif, Arslan Javed, Muhammad Yaqoob Gulzar, Muhammad Majid Politecn Torino Turin Italy Univ Sci & Technol China Hefei Peoples R China Univ Cent Punjab Lahore Pakistan

ISBN: (纸本)9781509055869

In this paper, General Purpose Graphical Processing Unit (GPGPU) based concurrent implementation of handwritten digit classifier is presented. Different styles of handwriting make it difficult to recognize a pattern but using neural network, it is not a difficult task to perform. Different softwares like torch and MATLAB provide the support of multiple training algorithms to train a network. By choosing an appropriate training algorithm for a specific application, speed of training can be increased. Furthermore, using computational power of GPUs, training and classification speed of neural network can be significantly improved. In this work, Modified National Institute of Standards and Technology (MNIST) database of handwritten digits is used to train the network. Accuracy and training time of digit classifier is evaluated for different algorithms and then concurrent training is performed by exploiting power of GPU. Trained parameters are imported and used for the concurrent classification with Compute Unified Device Architecture (CUDA) computing language which can be useful in numerous practical applications. Finally, the results of sequential and concurrent operations of training and classification are compared.

关键词： Concurrent parallel architectures Neural network Pattern recognition MATLAB Image Classification

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