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检索条件"任意字段=18th International Conference on Parallel and Distributed Computing Systems, PDCS 2005"

共 303 条记录，以下是151-160 订阅

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Optimized GPU Acceleration Algorithm of Convolutional Neural Networks for Target Detection

Optimized GPU Acceleration Algorithm of Convolutional Neural...

引用

18th IEEE international conference on High Performance computing and Communications (HPCC) / 14th IEEE international conference on Smart City (Smart City) / 2nd IEEE international conference on Data Science and systems (DSS)

作者： Li, Shijie Dou, Yong Lv, Qi Wang, Qiang Niu, Xin Yang, Ke Natl Univ Def Technol Natl Lab Parallel & Distributed Proc Changsha 410073 Hunan Peoples R China

ISBN: (纸本)9781509042975

Target detection is a hard real-time task for video and image processing. this task has recently been accomplished through the feedforward process of convolutional neural networks (CNN), which is usually accelerated by general-purpose graphic units (GPUs). However, there is a challenge for this task. the running speed remains to be improved. In this paper, we present an efficient image combination algorithm to accelerate the feedforward process of CNN. We run our experiments on a GTX980 card. Compared with that of cuDNNv3(a standard Nvidia deep learning library), a high speedup of 6.97x is obtained in the detection task.

关键词： Convolutional Neural Networks GPU Target detection

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Development of an IDS Hardware Unit for Real-time Learning Applications

Development of an IDS Hardware Unit for Real-time Learning A...

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18th IEEE international conference on Fuzzy systems

作者： Murakami, Masayuki Honda, Nakaji Univ Electrocommun Dept Syst Engn Tokyo 1828585 Japan

ISBN: (纸本)9781424435968

In artificial neural networks (ANNs) and fuzzy inference systems (FISs), hardware implementation is significantly effective in improving real-time performance by utilizing their parallel processing structures. thus, numerous hardware solutions for ANNs and FISs have been provided for time-critical control applications. the ink drop spread (IDS) method is a modeling technique that has been proposed as a new paradigm of soft computing. the structure of IDS models is similar to that of ANNs: they comprise distributed intermediate units referred to as IDS units. In this paper, the hardware design of the IDS unit is presented and it is demonstrated that the hardware implementation is effective in enhancing the real-time performance of IDS modeling systems.

关键词： Soft computing

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Proceedings of the 2012 IEEE 18th international conference on parallel and distributed systems, ICPADS 2012

Proceedings of the 2012 IEEE 18th International Conference o...

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18th IEEE international conference on parallel and distributed systems, ICPADS 2012

ISBN: (纸本)9780769549033

the proceedings contain 146 papers. the topics discussed include: a remote view system to allow real-time walkthrough;power control algorithm based on SNR cost function in cognitive radio system;visualization for anomaly detection and data management by leveraging network, sensor and GIS techniques;geographic routing with minimal local geometry;accelerating Volkov's hybrid implementation of Cholesky factorization on a Fermi GPU;GPU parallel computing of spherical panorama video stitching;GPU-based calculation for scattering characteristics of complex targets from background radiance in infrared spectrum;a GPU-based implementation of WRF MYNN PBL/surface layer scheme;parallel and distributed processing of remote sensing data on large displays;GPU-accelerated computation of 3D laser radar range imaging of arbitrary coarse targets;and design and development of an adaptive workflow-enabled spatial-temporal analytics framework.

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Scalability Issues for Self Similarity Join in distributed systems

Scalability Issues for Self Similarity Join in Distributed S...

引用

18th Euromicro international conference on parallel, distributed and Network-Based Processing (PDP)

作者： Gennaro, Claudio Rabitti, Fausto ISTI CNR Via G Moruzzi 1 I-56124 Pisa Italy

ISBN: (纸本)9780769539393

Efficient processing of similarity joins is important for a large class of data analysis and data-mining applications. this primitive finds all pairs of records within a predefined distance threshold of each other. However, most of the existing approaches have been based on spatial join techniques designed primarily for data in a vector space. Treating data collections as metric objects brings a great advantage in generality, because a single metric technique can be applied to many specific search problems quite different in nature. In this paper, we concentrate our attention on a special form of join, the Self Similarity Join, which retrieves pairs from the same dataset. In particular, we consider the case in which the dataset is split into subsets that are searched for self similarity join independently (e.g, as in a distributed computing environment). To this end, we formalize the abstract concept of epsilon-Cover, prove its correctness, and demonstrate its effectiveness by applying it to two real implementations on a real-life large dataset.

关键词： Vector spaces

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Optimizing Dynamic Programming on Graphics Processing Units via Data Reuse and Data Prefetch with Inter-Block Barrier Synchronization

Optimizing Dynamic Programming on Graphics Processing Units ...

引用

IEEE 18th international conference on parallel and distributed systems (ICPADS)

作者： Wu, Chao-Chin Wei, Kai-Cheng Lin, Ting-Hong Natl Changhua Univ Educ Dept Comp Sci & Informat Engn Changhua 500 Taiwan

ISBN: (纸本)9781467345651;9780769549033

Our previous study focused on accelerating an important category of DP problems, called nonserial polyadic dynamic programming (NPDP), on a graphics processing unit (GPU). In NPDP applications, the degree of parallelism varies significantly in different stages of computation, making it difficult to fully utilize the compute power of hundreds of processing cores in a GPU. To address this challenge, we proposed a methodology that can adaptively adjust the thread-level parallelism in mapping a NPDP problem onto the GPU, thus providing sufficient and steady degrees of parallelism across different compute stages. this work aims at further improving the performance of NPDP problems. Subproblems and data are tiled to make it possible to fit small data regions into shared memory and reuse the buffered data for each tile of subproblems, thus reducing the amount of global memory access. However, we found invoking the same kernel many times, due to data consistency enforcement across different stages, makes it impossible to reuse the tiled data in shared memory after the kernel is invoked again. Fortunately, the inter-block synchronization technique allows us to invoke the kernel exactly one time with the restriction that the maximum number of blocks is equal to the total number of streaming multiprocessors. In addition to data reuse, invoking the kernel only one time also enables us to prefetch data to shared memory across inter-block synchronization point, which improves the performance more than data reuse. We realize our approach in a real-world NPDP application - the optimal matrix parenthesization problem. Experimental results demonstrate invoking a kernel only one time cannot guarantee performance improvement unless we also reuse and prefetch data across barrier synchronization points.

关键词： dynamic programming GPU parallel computing tiling optimization

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Welcome Message from the conference Chair - pdcs 2006

Proceedings of the IASTED International Conference on Parall...

引用

Proceedings of the IASTED international conference on parallel and distributed computing and systems 2006年

作者： Zheng, S.Q.

No abstract available

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Detecting Precursor Patterns for Frequency Fluctuation in an Electrical Grid 18

Detecting Precursor Patterns for Frequency Fluctuation in an...

引用

18th IEEE/ACIS international conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed computing (SNPD)

作者： Islam, Md. Shahidul Pears, Russel Bacic, Boris Auckland Univ Technol Sch Engn Comp & Math Sci Auckland 1010 New Zealand

ISBN: (纸本)9781509055043

Precursor pattern identification addresses the problem of detecting warning signals in data that herald an impending event of extraordinary interest. In the context of electrical power systems, identifying precursors to fluctuations in power generation in advance would enable engineers to put in place measures that mitigate against the effects of such fluctuations. In this research we use the Morlet wavelet to transform a time series defined on electrical power generation frequency which was sampled at intervals of 30 seconds to identify potential precursor patterns. the power spectrum that results is then used to select high coefficient regions that capture a large faction of the energy in the spectrum. We then subjected the high coefficient regions together with a contrasting low coefficient region to a non-parametric ANOVA test and our results indicate that one high coefficient region dominates by predicting an overwhelming percentage of the variation that occurs during the subsequent fluctuation event. these results suggest that the wavelet is an effective mechanism to identify precursor activity in electricity time series data.

关键词： Precursor Pattern Frequency Fluctuation Wavelet Transform Non-Parametric ANOVA

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Efficient Multi-Keyword Ranked Query on Encrypted Data in the Cloud

Efficient Multi-Keyword Ranked Query on Encrypted Data in th...

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IEEE 18th international conference on parallel and distributed systems (ICPADS)

作者： Xu, Zhiyong Kang, Wansheng Li, Ruixuan Yow, KinChoong Xu, Cheng-Zhong Chinese Acad Sci Shenzhen Inst Adv Technol Beijing 100864 Peoples R China Huazhong Univ Sci & Technol Sch Comp Sci & Technol Wuhan Peoples R China Suffolk Univ Math & Comp Sci Dept Boston MA 02119 USA Wayne State Univ Dept Elect & Comp Engn Detroit MI 48202 USA

ISBN: (纸本)9781467345651;9780769549033

Cloud computing is becoming increasingly prevalent in recent years. It introduces an efficient way to achieve management flexibility and economic savings for distributed applications. To take advantage of computing and storage resources offered by cloud service providers, data owners must outsource their data onto public cloud servers which are not within their trusted domains. therefore, the data security and privacy become a big concern. To prevent information disclosure, sensitive data has to be encrypted before uploading onto the cloud servers. this makes plain text keyword queries impossible. As the total amount of data stored in public clouds accumulates exponentially, it is very challenging to support efficient keyword based queries and rank the matching results on encrypted data. Most current works only consider single keyword queries without appropriate ranking schemes. the multi-keyword query problem was being considered only recently. MRSE [1] is one of the first research works to define and address the problem of effective yet secure ranked multi-keyword search over encrypted cloud data. However, the keyword dictionary used in MRSE is static and must be rebuilt when the number of keywords in the dictionary increases. It also has severe out-of-order problems in the matching results and does not take the keyword access frequencies into account, which greatly affects its usability. In this paper, we propose a novel approach, called MKQE, to address these issues. Only minor changes in the dictionary structure have to be done when extra keywords are introduced. We also introduce new trapdoor generation and scoring algorithms to make in-order query results. Furthermore, the keyword access frequency is considered so as to select an adequate matching file set. We conduct extensive simulations and the results prove that our approach performs much better than previous solutions.

关键词： multi-keyword query ranked query encrypted data cloud computing heavy tail

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Batch-Based Flash Crowd Relaxation in Cloud-Assisted P2P Live Streaming 18

Batch-Based Flash Crowd Relaxation in Cloud-Assisted P2P Liv...

引用

18th IEEE/ACIS international conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed computing (SNPD)

作者： Jinbo, Shuji Alghazawy, Bahaa Aldeen Fujita, Satoshi Hiroshima Univ Dept Informat Engn Higashihiroshima 7398527 Japan

ISBN: (纸本)9781509055043

this paper proposes a batch-based method to effectively relax the flash crowd in P2P live streaming systems with the aid of the cloud. the role of the cloud is twofolds. the first one is to determine the concrete overlay structure of batches consisting of nodes waiting in the request queue which is restricted to be a multiple-spanning-tree. With this approach we could maximize the resource utilization in each batch without increasing the load of the tracker. the second one is to feed recently issued chunks to the gateway of batches before connecting them to the existing overlay. the performance of the proposed method is evaluated by simulation. the result of simulations indicates that: 1) the proposed method reduces the waiting time of conventional method by 80%, and 2) the amount of data fetched from the cloud could effectively be reduced by decreasing the size of batches.

关键词： P2P live streaming cloud-assisted flash crowd

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Decision Model for Identity Management Product Selection Using Fuzzy AHP 18

Decision Model for Identity Management Product Selection Usi...

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18th IEEE/ACIS international conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed computing (SNPD)

作者： Noradachanon, Noraset Senivongse, Twittie Chulalongkorn Univ Fac Engn Dept Comp Engn Software Engn Program Bangkok Thailand

ISBN: (纸本)9781509055043

Identity management (IDM) refers to a security discipline that employs technologies to manage information about the identity of users and control their access to organization resources. Various IDM products are in the market to offer corporate customers productivity and security while lowering costs of identity management. System integrators who implement the IDM solutions for their corporate customers often face problems when choosing the right IDM products for integrating with the customers' enterprise systems. this paper proposes a decision model for IDM product selection which is used in evaluating and ranking IDM products based on the proposed customer requirements questionnaire. the model is comprehensive in that its decision criteria comprise not only the technical specifications of the products but also other important aspects including price and accountability of system integrators and product vendors. Based on the decision model, product selection is conducted using a multi-criteria decision making technique called fuzzy analytic hierarchy process (fuzzy AHP). In an evaluation, a leading system integrator company in thailand applies the proposed approach to IDM product selection for its customer and the result is quite satisfactory.

关键词： identity management multi-criteria decision making analytic hierarchy process fuzzy set

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