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检索条件"任意字段=12th Euromicro Conference on Parallel, Distributed and Network-Based Processing"

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Geo-distributed BigData processing for Maximizing Profit in Federated clouds environment 26

Geo-distributed BigData Processing for Maximizing Profit in ...

引用

26th euromicro International conference on parallel, distributed, and network-based processing (PDP)

作者： Gouasmi, thouraya Louati, Wajdi Kacem, Ahmed Hadj Univ Sfax ReDCAD Lab Sfax Tunisia

ISBN: (纸本)9781538649756

Managing and processing BigData in geo-distributed datacenters gain much attention in recent years. Despite the increasing attention on this topic, most efforts have been focused on user-centric solutions, and unfortunately much less on the difficulties encountered by Cloud providers to improve their profits. Highly efficient framework for geo-distributed BigData processing in cloud federation environment is a crucial solution to maximize profit of the cloud providers. the objective of this paper is to maximize the profit for cloud providers by minimizing costs and penalty. this work proposes to transfer compute (computations) to geo-distributed data and outsourcing only the desired data to idles resources of federated clouds in order to minimize job costs;and proposes a jobs reordering dynamic approach to minimize the penalties costs. the performance evaluation proves that our proposed algorithm can maximize profit, reduce the MapReduce jobs costs and improve utilization of clusters resources.

关键词： Federated clouds Geo-distributed MapReduce Profit Maximizing

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TMbarrier: Speculative Barriers Using Hardware Transactional Memory 26

TMbarrier: Speculative Barriers Using Hardware Transactional...

引用

26th euromicro International conference on parallel, distributed, and network-based processing (PDP)

作者： Pedrero, Manuel Gutierrez, Eladio Plata, Oscar Univ Malaga Dept Comp Architecture Malaga Spain

ISBN: (纸本)9781538649756

Barrier is a very common synchronization method used in parallel programming. Barriers are used typically to enforce a partial thread execution order, since there may be dependences between code sections before and after the barrier. this work proposes TMbarrier, a new design of a barrier intended to be used in transactional applications. TMbarrier allows threads to continue executing speculatively after the barrier assuming that there are not dependences with safe threads that have not yet reached the barrier. Our design leverages transactional memory (TM) (specifically, the implementation offered by the IBM POWER8 processor) to hold the speculative updates and to detect possible conflicts between speculative and safe threads. Despite the limitations of the best-effort hardware TM implementation present in current processors, experiments show a reduction in wasted time due to synchronization compared to standard barriers.

关键词： Hardware Transactional Memory Speculation IBM POWER8 parallel Computing

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O-TF and O-FTF, Optical Fault-Tolerant DCNs 26

O-TF and O-FTF, Optical Fault-Tolerant DCNs

引用

26th euromicro International conference on parallel, distributed, and network-based processing (PDP)

作者： Abadi, Saeedeh Akbari Rokn Koohi, Somayyeh Sharif Univ Technol Dept Comp Engn Tehran Iran

ISBN: (纸本)9781538649756

Performance of a data center is a function of three features;bandwidth, latency, and reliability. By adopting optical technology in data center network, bandwidth increment, in addition to reduction of transmission latency and power consumption, is achieved. Unfortunately, fault tolerance of the optical networks has raised less attention so far. So in this paper, we propose a fault-tolerant, scalable, and high-performance optical architecture built upon previously proposed O-TF network, with the goal of redundancy optimization and reducing the minimum number of wavelength channels required for non-blocking functionality of the network. Moreover, reducing network diameter, in O-FTF network compared to O-TF and Wavecube networks, has led to higher network performance at the presence of network failures.

关键词： Optical interconnection network Data Center fault-tolerant non-blocking high-performance

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parallelization of security event correlation based on accounting of event type links 26

Parallelization of security event correlation based on accou...

引用

26th euromicro International conference on parallel, distributed, and network-based processing (PDP)

作者： Kotenko, Igor Fedorchenko, Andrey Saenko, Igor Kushnerevich, Alexey Russian Acad Sci SPIIRAS St Petersburg Inst Informat & Automat St Petersburg Russia ITMO Univ St Petersburg Natl Res Univ Informat Technol Mech St Petersburg Russia

ISBN: (纸本)9781538649756

the paper proposes a novel approach to parallel data processing for solving security event correlation problems based on Big Data technologies. Different security event correlation methods and problems, as well as big data technologies applicable for security monitoring are considered. the main attention is paid to the problems of identifying the links between security event types and assessing the dependence of the link strength on event distribution in time. Implementation of correlation problem solutions on the Spark platform is described, and the results of experimental assessment of security event correlation processes are given.

关键词： security event correlation Pearson correlation coefficient SIEM system Big Data parallel data processing

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Divisible Load Scheduling of Image processing Applications on the Heterogeneous Star network Using a New Genetic Algorithm 26

Divisible Load Scheduling of Image Processing Applications o...

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26th euromicro International conference on parallel, distributed, and network-based processing (PDP)

作者： Aali, Sahar Nikbakht Shahhosseini, Hadi Shahriar Bagherzadeh, Nader Iran Univ Sci & Technol Tehran Iran Univ Calif Irvine Irvine CA USA

ISBN: (纸本)9781538649756

the divisible load scheduling of image processing applications on the heterogeneous star network is addressed in this paper. In our platform, processors and links have different speeds. Also the computation and communication overheads are considered. A new genetic algorithm for minimizing the processing time of low level image applications using divisible load theory is introduced. A closed form solution for the processing time and the image fractions that should be assigned to each processor are obtained. the optimum number of participating processors and the optimal sequence for load distribution with a new genetic algorithm are derived. the effect of different image and kernel sizes on processing time and speed up are investigated. Finally, to indicate the efficiency of our algorithm, several numerical experiments are presented.

关键词： Divisible load scheduling local operation image fractions load distibution sequence genetic algorithm

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Resizing of Heterogeneous Platforms and the optimization of parallel applications 26

Resizing of Heterogeneous Platforms and the optimization of ...

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26th euromicro International conference on parallel, distributed, and network-based processing (PDP)

作者： Beji, Moussa Achour, Sami Fac Sci Tunis Dept Comp Sci Tunis Tunisia Higher Inst Appl Sci & Technol Sousse Dept Comp Sci Sousse Tunisia

ISBN: (纸本)9781538649756

With the birth of multi-cluster platforms, scheduling and finding the optimal number of resources (clusters, processors) to execute an application constitute very critical problems. In this paper, we address the need for scheduling techniques for parallel task applications on this kind of platforms and we propose a new strategy for scheduling sequential task graphs based on existing heuristics that have proved to be efficient on homogeneous environments. the contribution of this paper lies in determining the appropriate clusters which participate to compute a given application. Our solution is composed of three steps: Firstly, determining of the computing clusters, secondly, determining the optimal number of processors in each cluster, finally place the tasks on the appropriate processors. Simulation results, based on both randomly generated graphs and real configuration platforms, show that the proposed approach provides interesting trade-off between makespan and resource consumption.

关键词： multi-cluster paltforms parallel task graph makespan scheduling

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Performance and Energy Consumption Analysis of Coprocessors using Different Programming Models 26

Performance and Energy Consumption Analysis of Coprocessors ...

引用

26th euromicro International conference on parallel, distributed, and network-based processing (PDP)

作者： Goncalves, Robson Girardi, Alessandro Schepke, Claudio Fed Univ Pampa UNIPAMPA Alegrete Technol Campus Alegrete RS Brazil

ISBN: (纸本)9781538649756

the optimization of the relation between performance and energy consumption is a strong requirement mainly in high performance environments. the top 10 Green500 super-computers use accelerators/coprocessors as primary approach to increase the performance while reducing energy consumption. this paper presents a study on the main factors that impact this relationship, evaluating and comparing Intel programming models on an Intel Xeon Phi coprocessor architecture. the methodology applied in this work consists of evaluating performance and energy consumption on execution scenarios using Linpack and HPL 2.1 benchmarks. these scenarios consider various environment parameters and execution on the Intel host, offload and native programming models. Experimental results indicate that the host and offload models are more efficient in the performance per energy consumption relationship with shared memory and distributed memory, whereas the native model demonstrated better efficiency in energy consumption.

关键词： Energy consumption Coprocessors Benchmark testing Programming Memory management Monitoring Computational modeling

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Predicting the Price of Bitcoin Using Machine Learning 26

Predicting the Price of Bitcoin Using Machine Learning

引用

26th euromicro International conference on parallel, distributed, and network-based processing (PDP)

作者： McNally, Sean Roche, Jason Caton, Simon Natl Coll Ireland Sch Comp Dublin 1 Ireland Dublin Business Sch Dublin 2 Ireland

ISBN: (纸本)9781538649756

the goal of this paper is to ascertain with what accuracy the direction of Bitcoin price in USD can be predicted. the price data is sourced from the Bitcoin Price Index. the task is achieved with varying degrees of success through the implementation of a Bayesian optimised recurrent neural network (RNN) and a Long Short Term Memory (LSTM) network. the LSTM achieves the highest classification accuracy of 52% and a RMSE of 8%. the popular ARIMA model for time series forecasting is implemented as a comparison to the deep learning models. As expected, the non-linear deep learning methods outperform the ARIMA forecast which performs poorly. Finally, both deep learning models are benchmarked on both a GPU and a CPU with the training time on the GPU outperforming the CPU implementation by 67.7%.

关键词： Bitcoin Deep Learning GPU Recurrent Neural network Long Short Term Memory ARIMA

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Lazy Allocation and Transfer Fusion Optimization for GPU-based Heterogeneous Systems 26

Lazy Allocation and Transfer Fusion Optimization for GPU-bas...

引用

26th euromicro International conference on parallel, distributed, and network-based processing (PDP)

作者： Li, Lu Kessler, Christoph Linkoping Univ IDA Linkoping Sweden

ISBN: (纸本)9781538649756

We present two memory optimization techniques which improve the efficiency of data transfer over PCIe bus for GPU-based heterogeneous systems, namely lazy allocation and transfer fusion optimization. Both are based on merging data transfers so that less overhead is incurred, thereby increasing transfer throughput and making accelerator usage profitable also for smaller operand sizes. We provide the design and prototype implementation of the two techniques in CUDA. Microbench-marking results show that especially for smaller and medium-sized operands significant speedups can be achieved. We also prove that our transfer fusion optimization algorithm is optimal.

关键词： adaptive message fusion GPU CUDA lazy memory allocation memory transfer optimization

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A Secure distributed Framework for Agglomerative Hierarchical Clustering Construction 26

A Secure Distributed Framework for Agglomerative Hierarchica...

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26th euromicro International conference on parallel, distributed, and network-based processing (PDP)

作者： Hamidi, Mona Sheikhalishahi, Mina Martinelli, Fabio Univ Siena Dipartimento Ingn Informaz & Sci Matemat Siena Italy CNR Ist Informat & Telemat Pisa Italy

ISBN: (纸本)9781538649756

this paper presents a general framework for constructing any agglomerative hierarchical clustering algorithm over partitioned data. It is assumed that data is distributed between two (or more) parties horizontally, such that for mutual benefits the participated parties are willing to identify the clusters' structure on their data as a whole, but for privacy restrictions, they avoid to share the original datasets. To this end, in this study, we propose general algorithms based on secure scalar product and secure hamming distance computation to securely compute the desired criteria for shaping the clusters' scheme. the proposed approach covers all possible secure agglomerative hierarchical clustering construction when data is distributed between two (or more) parties, including both numerical and categorical data.

关键词： Privacy Hierarchical Clustering Secure Two-Party Computation Collaborative Clustering

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