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检索条件"任意字段=13th IEEE International Symposium on Parallel and Distributed Processing with Applications"

共 2573 条记录，以下是71-80 订阅

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parallel Skyline Computation for Partially Ordered Domains 15

Parallel Skyline Computation for Partially Ordered Domains

引用

15th ieee international symposium on parallel and distributed processing with applications (ISPA) / 16th ieee international Conference on Ubiquitous Computing and Communications (IUCC)

作者： Yin, Bo Gu, Ke Changsha Univ Sci & Technol Sch Comp & Commun Engn Changsha Hunan Peoples R China

ISBN: (纸本)9781538637906

the skyline queries help users handle the huge amount of available data by finding a set of interesting points. As the dataset sizes are constantly increasing and skyline queries are computationally expensive, it is critical to compute such queries by utilizing parallelism. Existing works deal exclusively with the totally ordered attribute domains. In this paper, we present a framework, named PSLP, for parallel skyline evaluation for data with both totally and partially ordered domains. We introduce a new partial-to-order mapping scheme that guarantees the correctness of the mapping by preserving incomparability and preference with low mapping cost. We also propose a novel logical partitioning for parallel processing where data space are partitioned according to their incomparability and preference relationships by using a pivot point. the logical partitioning can prune away partitions that do not contain any skyline point at the partitioning processing. An extensive performance evaluation confirms the efficiency and effectiveness of the proposed approach.

关键词： skyline queries partially-ordered domain parallel computation data partitioning

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Designing Bit-Reproducible Portable High-Performance applications

Designing Bit-Reproducible Portable High-Performance Applica...

引用

ieee 28th international parallel & distributed processing symposium (IPDPS)

作者： Arteaga, Andrea Fuhrer, Oliver Hoefler, Torsten Swiss Fed Inst Technol Zurich Switzerland Fed Off Meteorol & Climatol MeteoSwiss Zurich Switzerland

ISBN: (纸本)9780769552071

Bit-reproducibility has many advantages in the context of high-performance computing. Besides simplifying and making more accurate the process of debugging and testing the code, it can allow the deployment of applications on heterogeneous systems, maintaining the consistency of the computations. In this work we analyze the basic operations performed by scientific applications and identify the possible sources of non-reproducibility. In particular, we consider the tasks of evaluating transcendental functions and performing reductions using non-associative operators. We present a set of techniques to achieve reproducibility and we propose improvements over existing algorithms to perform reproducible computations in a portable way, at the same time obtaining good performance and accuracy. By applying these techniques to more complex tasks we show that bit-reproducibility can be achieved on a broad range of scientific applications.

关键词： determinism reproducibility parallelism ieee-754 standard

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A Shape-Shifting distributed Meta-Algorithm for Modular Robots 12

A Shape-Shifting Distributed Meta-Algorithm for Modular Robo...

引用

12th ieee international symposium on parallel and distributed processing with applications (ISPA)

作者： Mabed, Hakim Bourgeois, Julien CNRS UFC FEMTO ST UMR 6174 F-25201 Montbeliard France

ISBN: (纸本)9781479942930

Novel platforms of modular robot systems have been developed with important applications in safety, transportation and sensing domains. In such systems, modular robots are able to change their organization in order to obtain different shapes. the conception of distributed programs allowing the "optimal" reorganization of a set of robots into a specific shape appears as a very challenging problem. In this paper we present an original distributed meta-algorithm for micro-robots shape-shifting problem. We show that this meta-algorithm, described as a general functioning schema, presents a good framework to easily conceive distributed algorithms for shape-shifting problems. We also prove the facility to instantiate the algorithm for special target shapes and we give an adaptation of the algorithm to reach any horizontally convex form. the presented meta-algorithm presents two main advantages: first, there is no need to exact positioning of the robots and secondly, the memory storage and communication requirements are significantly reduced.

关键词： distributed algorithm self-configuration modular micro-robots shape-shifting

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Automatic tuning of a parallel pattern library for heterogeneous systems with Intel Xeon Phi 12

Automatic tuning of a parallel pattern library for heterogen...

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12th ieee international symposium on parallel and distributed processing with applications (ISPA)

作者： Dokulil, Jiri Benkner, Siegfried Univ Vienna Res Grp Sci Comp A-1010 Vienna Austria

ISBN: (纸本)9781479942930

Pattern libraries are important tools for high productivity application development. their struggle for best performance is complicated by the fact that they are used to execute user-provided code, which is not known during their creation. this makes pattern libraries good candidate for automatic software tuning. In this paper, we deal with automatic online parameter tuning of the HyPHI hybrid pattern library for heterogeneous systems equipped with the Intel Xeon Phi coprocessors. We propose a framework that can be used to combine a pattern library with an existing tuning library in a practical and efficient way. Our experiments show that tuning can noticeably improve the performance of the library and it introduces very little overhead.

关键词： Computerarchitecture Coprocessors Databases Kernel Libraries Runtime Tuning IntelXeonPhi automaticsoftwaretuning parallelpatternlibraries Coprocessors Libraries tuning HETEROGENEOUS SYSTEM Runtime Database Kernel parallel mode Self tuning

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Real-Time Ship detection from Infrared Images through Multi-feature Fusion 19

Real-Time Ship detection from Infrared Images Through Multi-...

引用

19th ieee international symposium on parallel and distributed processing with applications (ieee ISPA)

作者： Miao, Rui Jiang, Hongxu Tian, Fangzheng Li, Xiaobin Zhang, Yonghua Dong, Dong Beihang Univ Hangzhou Innovat Inst Beijing Key Lab Digital Media Beijing Peoples R China

ISBN: (纸本)9781665435741

Real-time ship detection from remote sensing imagery it is a great challenge due to the complex scene, the changeable characteristics of ship target, and the uncontrollable interference factors. In this letter, an infrared ship detection algorithm based on multi-feature fusion is proposed. Based on the fully analysis of the target features, the proposed algorithm combines the cascade rejection mechanism with multi-features through a cascade linear classifier from simple to complex, and uses fine features to accurately distinguish the target from the complex background. Large number of experimental results show that the proposed method can achieve better results in detection performance and real-time processing.

关键词： Image processing Real-time Multi-feature Fusion

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Improving Cryptanalytic applications with Stochastic Runtimes on GPUs

Improving Cryptanalytic Applications with Stochastic Runtime...

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35th ieee international parallel and distributed processing symposium (IPDPS)

作者： Oden, Lena Keller, Joerg Fernuniv Fac Math & Comp Sci Hagen Germany

ISBN: (纸本)9781665435772

We investigate cryptanalytic applications comprised of many independent tasks that exhibit a stochastic runtime distribution. We compare four algorithms for executing such applications on GPUs. We demonstrate that for different distributions, problem sizes, and platforms the best strategy varies. We support our analytic results by extensive experiments on two different GPUs, from different sides of the performance spectrum: A high performance GPU (Nvidia Volta) and an energy saving system on chip (Jetson Nano).

关键词： Cryptanalytic applications Stochastic Runtime Graphics processing Units Performance Evaluation

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引用

13th international Conference on parallel and distributed Computing, applications, and Technologies (PDCAT)

作者： Zhang, Jian Yuan, Chunfeng Huang, Yihua Nanjing Univ Natl Key Lab Novel Software Technol Dept Comp Sci & Technol Nanjing 210093 Jiangsu Peoples R China

ISBN: (纸本)9780769548791

Measures of graph similarity have a broad range of applications but involve compute-intensive process. Similarity flooding algorithm is an efficient algorithm for comparing the similarity of graphs of small size and small datasets. However, nowadays more and more large-scale graph applications emerge and existing stand-alone similarity flooding algorithm cannot efficiently conduct the similarity comparison process for large scale graph datasets in acceptable time. this paper presents a parallelized similarity flooding algorithm with MapReduce for large-scale graph datasets. the experimental results demonstrate that the parallelized algorithm achieves significant performance improvement compared to the stand-alone similarity flooding algorithm. Experimental results also reveal that the parallelized algorithm can obtain excellent speedup when the size of cluster increases.

关键词： similarity flooding algorithm large-scale graph data parallelized algorithm MapReduce

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Proceedings - 2023 ieee international Conference on parallel and distributed processing with applications, Big Data and Cloud Computing, Sustainable Computing and Communications, Social Computing and Networking, ISPA/BDCloud/SocialCom/SustainCom 2023

Proceedings - 2023 IEEE International Conference on Parallel...

引用

21st ieee international symposium on parallel and distributed processing with applications, 13th ieee international Conference on Big Data and Cloud Computing, 16th ieee international Conference on Social Computing and Networking and 13th international Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

ISBN: (纸本)9798350329223

the proceedings contain 153 papers. the topics discussed include: transaction data management optimization based on multi-partitioning in blockchain systems;semi-asynchronous federated learning optimized for NON-IID data communication based on tensor decomposition;HKTGNN: hierarchical knowledge transferable graph neural network-based supply chain risk assessment;DQR-TTS: semi-supervised text-to-speech synthesis with dynamic quantized representation;deep reinforcement learning-based network moving target defense in DPDK;iNUMAlloc: towards intelligent memory allocation for AI accelerators with NUMA;and predictive queue-based low latency congestion detection in data center networks.

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parallel Computing in DNNs Using CPU and MIC 15

Parallel Computing in DNNs Using CPU and MIC

引用

15th ieee international symposium on parallel and distributed processing with applications (ISPA) / 16th ieee international Conference on Ubiquitous Computing and Communications (IUCC)

作者： Fan, Sijiang Zhang, Shiqing He, Ximing Fei, Jiawei Shen, Li Wang, Zhiying Natl Univ Def Technol Sch Comp State Key Lab High Performance Comp Changsha Hunan Peoples R China

ISBN: (纸本)9781538637906

Acceleration for the training process of Deep Neural Networks (DNNs) has been the focus of deep learning field. there were many researches of accelerating deep learning on different platforms. Among them, Intel Xeon Phi Co-processor is a many-core platform which provides both strong programmability and high performance. But previous work about Intel Many Integrated Core (MIC) focused on parallel computing only in MIC. In this paper, we speed up the training process of DNNs applied for automatic speech recognition with CPU+MIC architecture. In this architecture, the training process of DNNs is executed both on MIC and CPU. We apply several optimization methods for I/O and calculation and set up experiments to approve these methods. Putting all methods together, results show that our optimized algorithm acquires about 20x speedup compared with the original sequential algorithm on CPU which uses one core.

关键词： DNNs Hybrid Architecture parallel Computing Load Balance

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NetANNS: A High-Performance distributed Search Framework Based On In-Network Computing 19

NetANNS: A High-Performance Distributed Search Framework Bas...

引用

19th ieee international symposium on parallel and distributed processing with applications (ieee ISPA)

作者： Zhang, Penghao Pan, Heng Li, Zhenyu Xie, Gaogang Cui, Penglai Chinese Acad Sci Inst Comp Technol Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Purple Mt Labs Nanjing Peoples R China Chinese Acad Sci Comp Network Informat Ctr Beijing Peoples R China

ISBN: (纸本)9781665435741

Approximate nearest neighbor search (ANNS) is the most basic and important algorithm in Database, Machine Learning and other applications. With the expansion of cloud computing, the academia focuses on the study of how to optimize distributed frameworks based on approximate nearest neighbor search such as MapReduce, and Memcached. We implement a new distributed ANNS search framework (NetANNS). the main contributions of NetANNS are to accelerate the data preprocessing with programmable switch, and integrate a variety of efficient ANNS algorithms so that it can choose the most suitable algorithm for each datasets. the experiments show that the search efficiency of NetANNS is about 2x than the common distributed ANNS frameworks which are implemented based on the framework of MapReduce.

关键词： approximate nearest neighbor search distributed search in-network computation

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