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A Distributed Framework for Event Detection in Video Surveillance Context

A Distributed Framework for Event Detection in Video Surveil...

引用

international conference on P2P, parallel, Grid, Cloud and Internet Computing (3PGCIC)

作者： Fabio Persia Daniela D'Auria Faculty of Computer Science Free University of Bozen Italy DIETI University of Naples Federico II Italy

In latest years modern world's needs of safety caused a speed spreading of video surveillance systems, more and more frequently collocated in the most crowded places. thus, a lot of theoretical approaches working with data coming from heterogeneous sources and defining some very complex event detection algorithms have been proposed in the literature. In this paper, we present a distributed framework for event detection in video surveillance context. the overall process is described, starting from the video frames captured by different kinds of sensors and cameras till at the end some high-level event detection algorithms performed in a distributed environment for finding potentially dangerous activities are applied. the conducted experiments confirm the efficiency achieved by our distributed framework.

关键词： Video surveillance Cameras Sensors Image processing Event detection Context Libraries

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parallel Kirchhoff pre-stack depth migration on large high performance clusters 15th

Parallel Kirchhoff pre-stack depth migration on large high p...

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15th international conference on algorithms and architectures for parallel processing, ICA3PP 2015

作者： Li, Chao Wang, Yida Zhao, Changhai Yan, Haihua Zhang, Jianlei School of Computer Science and Engineering Beihang University Beijing100191 China Research and Development Center BGP Inc. CNPC ZhuozhouHebei072751 China

ISBN: (纸本)9783319271361

Kirchhoff Pre-Stack Depth Migration (KPSDM) is a widely used algorithm for seismic imaging in petroleum industry. To provide higher FLOPS, modern high performance clusters are equipped with more computing nodes and more cores for each node. the evolution style of clusters leads to two problems for upper layer applications such as KPSDM: (1) the increasing disparity of the I/O capacity and computing performance is becoming a bottleneck for higher scalability;(2) the decreasing Mean Time Between Failures (MTBF) limits the availability of the applications. In this paper, we present an optimized parallel implementation of KPSDM to adapt to modern clusters. First, we convert the KPSDM into a clear and simple task-based parallel application by decomposing the computation along two dimensions: the imaging space and seismic data. then, those tasks are mapped to computing nodes that are organized using a two-level master/worker architecture to reduce the I/O workloads. And each task is further parallelized using multi-cores to fully utilize the computing resources. Finally, fault tolerance and checkpoint are implemented to meet the availability requirement in production environments. Experimental results with practical seismic data show that our parallel implementation of KPSDM can scale smoothly from 51 nodes (816 cores) to 211 nodes (3376 cores) with low I/O workloads on the I/O sub-system and multiple process failures can be tolerated efficiently. © Springer international Publishing Switzerland 2015.

关键词： Fault tolerance

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A New parallel Symmetric Tridiagonal Eigensolver Based on Bisection and Inverse Iteration algorithms for Shared-Memory Multi-core Processors

A New Parallel Symmetric Tridiagonal Eigensolver Based on Bi...

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international conference on P2P, parallel, Grid, Cloud and Internet Computing (3PGCIC)

作者： Hiroyuki Ishigami Kinji Kimura Yoshimasa Nakamura Graduate School of Informatics Kyoto University Kyoto Japan

ISBN: (纸本)9781467394741

In order to accelerate the subset computation of eigenpairs for real symmetric tridiagonal matrices on shared-memory multi-core processors, a parallel symmetric tridiagonal eigensolver is proposed, which computes eigenvalues of target matrices using the parallel bisection algorithm and computes the corresponding eigenvectors using the block inverse iteration algorithm with reorthogonalization (BIR algorithm). the BIR algorithm is based on the simultaneous inverse iteration (SI) algorithm, which is a variant of the inverse iteration algorithm, and is introduced to a block parameter. Since the BIR algorithm is mainly composed of the matrix multiplications, the proposed eigensolver is expected to accelerate the computation of eigenpairs even on massively parallel computers. Numerical experiments on shared-memory multi-core processors show that the BIR algorithm is faster than the SI algorithm and achieves the good parallel efficiency. In addition, many cases of the numerical experiments also show that the proposed eigensolver, including the parallel bisection and the BIR algorithm, is more accurate than the parallel implementation of other eigensolvers, such as the QR iteration algorithm, the divide-and-conquer algorithm, and the multiple relatively robust representations algorithm.

关键词： Eigenvalues and eigenfunctions Symmetric matrices Clustering algorithms Computational efficiency Approximation algorithms Multicore processing Silicon

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Complexity Estimates of a SHA-1 Near-Collision Attack for GPU and FPGA

Complexity Estimates of a SHA-1 Near-Collision Attack for GP...

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international conference on Availability, Reliability and Security, ARES

作者： Jürgen Fuß Stefan Gradinger Bernhard Greslehner-Nimmervoll Robert Kolmhofer Research Group Sichere Informationssysteme FH OÖ Research and Development Hagenberg Austria Dept. f. Sichere Informationssysteme University of Applied Sciences Upper Austria Hagenberg Austria

the complexity estimate of a hash collision algorithm is given by the unit hash compressions. this paper shows that this figure can lead to false runtime estimates when accelerating the algorithm by the use of graphics processing units (GPU) and field-programmable gate arrays (FPGA). For demonstration, parts of the CPU reference implementation of Marc Stevens' SHA-1 Near-Collision Attack are implemented on these two accelerators by taking advantage of their specific architectures. the implementation, runtime behavior and performance of these ported algorithms are discussed, and in conclusion, it is shown that the acceleration results in different complexity estimates for each type of coprocessor.

关键词： Graphics processing units Field programmable gate arrays Complexity theory Instruction sets Kernel Message systems throughput

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Analysis of Computational Models and Application Characteristics Suitable for Reconfigurable FPGAs

Analysis of Computational Models and Application Characteris...

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international conference on P2P, parallel, Grid, Cloud and Internet Computing (3PGCIC)

作者： Darshika G. Perera Kin Fun Li University of Colorado at Colorado Springs Colorado USA University of Victoria Victoria BC Canada

ISBN: (纸本)9781467394741

With the proliferation of mobile and handheld devices, many applications have found their way into these devices. In order to process the applications on mobile systems, effectively and efficiently, optimized hardware-software architectures are needed. Our previous analysis illustrated that FPGA-based reconfigurable systems provide the most viable option to support application on mobile devices. However, computation models and application characteristics also play significant roles in determining whether FPGA-based reconfigurable hardware is indeed a good match for specific applications on a mobile or embedded platform. In this work, we investigate and present computation models and application characteristics that could potentially benefit from this hardware and discuss the how's and why's.

关键词： Computational modeling Hardware Field programmable gate arrays Mobile communication Pipeline processing Data models Fitting

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Indexing GPU acceleration for solutions approximation of the Laplace equation

Indexing GPU acceleration for solutions approximation of the...

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Colombian conference on Computing (CCC)

作者： Manuel Alejandro Tamayo Monsalve Nubia Liliana Montes Castrillon Reinel Tabares Soto Gustavo Osorio Universidad Nacional de Colombia Sede Manizales Universidad de Caldas Manizales CO

this paper presents the use of two-dimensional indexation existing in graphics processing units (GPU), to accelerate approximation algorithms of system solutions of partial differential equations. these approximation use recurrent equations where dependence of the near data plays an important role in the calculation speed. For these calculations large amount of data are involved, as well as frequently memory accesses. therefore, using computational structures that allow you to realize operations in a parallel and concurrent way to process the information more quickly is convenient. Also the memory indexation capacity enables the generation of better acceleration. 3 different architectures are compared, and contrasted against the sequential process on CPU. the results shows how the accelerations up until 9x can be achieve on the case of the Laplace equation in two dimensions.

关键词： Graphics processing units Electronic mail VLIW Acceleration Approximation methods High definition video Laplace equations

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Fast data-dependence profiling by skipping repeatedly executed memory operations 15th

Fast data-dependence profiling by skipping repeatedly execut...

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15th international conference on algorithms and architectures for parallel processing, ICA3PP 2015

作者： Li, Zhen Beaumont, Michael Jannesari, Ali Wolf, Felix Technische Universität Darmstadt Darmstadt64289 Germany RWTH Aachen University Aachen52062 Germany

ISBN: (纸本)9783319271392

Nowadays, more and more program analysis tools adopt pro- filing approaches in order to obtain data dependences because of their ability of tracking dynamically allocated memory, pointers, and array indices. However, dependence profiling suffers from high time overhead. To lower the overhead, former dependence profiling techniques either exploit features of the specific program analyses they are designed for, or let the profiling process run in parallel. Although they successfully lowered the time overhead of dependence profiling by a certain amount, none of them have tried to solve the fundamental problem that causes the high time overhead: the memory operations that are repeatedly executed in loops. In most of the time, these memory operations lead to exactly the same data dependences. However, a profiling method has to profile all these memory operations over and over again in order to not miss a single dependence that may occur just once. In this paper, we present a method that allow a dependence profiling technique to skip memory operations that are repeatedly executed in loops without missing any sin- gle data dependence. Our method works with all types of loops and does not require any prepossessing like source annotation of the input code. Experiment results show that our method can lower the time overhead of data-dependence profiling by up to 52%. © Springer international Publishing Switzerland 2015.

关键词： parallel programming

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Joint redundancy and inspection-based maintenance optimization for series-parallel system 15th

Joint redundancy and inspection-based maintenance optimizati...

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15th international conference on algorithms and architectures for parallel processing, ICA3PP 2015

作者： Yao, Yuan He, Pan Zheng, Zhihao Tan, Chun Yuan, Yue Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing400714 China

ISBN: (纸本)9783319271361

While researchers have concentrated on the optimization of joint redundancy and maintenance mechanism, maintenance in computing systems is quite different from that in traditional systems. Considering a routine monitoring and inspection mechanisms is conducted to detect component status and trigger repair process, this paper pays attention to the optimization problem of joint redundancy and inspection-based maintenance mechanism. After conducting steady state analysis on subsystems using inspection-based maintenance, shared repair facility and component redundancy, optimization model is built to search appropriate system structure and maintenance policy which maximizes system performance while meeting availability and cost constraints. Due to the complexity of uncertain optimization model, genetic algorithm is used to search optimal solution, using triple-element encoding mechanism and specifically designed operators. Illustrative examples are conducted to show that the optimization model and corresponding solution technique could be used to search optimal system configuration under given constraints and different cost constraints would lead to different optimization result while meeting availability constraints. © Springer international Publishing Switzerland 2015.

关键词： Redundancy

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Identifying repeated interleavings to improve the efficiency of concurrency bug detection 15th

Identifying repeated interleavings to improve the efficiency...

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15th international conference on algorithms and architectures for parallel processing, ICA3PP 2015

作者： Wu, Zhendong Lu, Kai Wang, Xiaoping Science and Technology on Parallel and Distributed Processing Laboratory College of Computer National University of Defense Technology Changsha410073 China

ISBN: (纸本)9783319271392

Detecting concurrency bugs is becoming increasingly important. Many pattern-based concurrency bug detectors focus on the specific types of interleavings that are correlated to concurrency bugs. To detect multiple types of concurrency bugs, general detectors focus on multiple types of interleaving patterns, including data race pattern, atomicity violation pattern, and atomic-set violation pattern. Unfortunately, they suffer from redundant analysis due to repeated interleavings, which may affect the efficiency of concurrency bug detection. Hence, we propose an approach to identify the repeated interleavings. To the best of our knowledge, this is the first approach that can prune repeated interleavings to improve the efficiency of concurrency bug detection. We apply our approach to existing general detectors (PECAN and Maple) to avoid analyzing repeated interleavings. We evaluated the general detectors with and without our approach, respectively. the experimental results show that the bug detection results are not affected. With our approach, the bug detection time of PECAN and Maple are reduced by 40.0% and 44.4%, respectively. Additionally, our approach does not affect the overhead of bug detection, and consumes only a little memory. © Springer international Publishing Switzerland 2015.

关键词： Efficiency

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DFIS: A scalable distributed fingerprint identification system 15th

DFIS: A scalable distributed fingerprint identification syst...

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15th international conference on algorithms and architectures for parallel processing, ICA3PP 2015

作者： Zhao, Yunxiang Zhang, Wanxin Li, Dongsheng Huang, Zhen National Laboratory for Parallel and Distributed Processing College of Computer National University of Defence Technology ChangshaHunan410073 China

ISBN: (纸本)9783319271361

Fingerprint has been widely used in a variety of biometric identification systems. However, with the rapid development of fingerprint identification systems, the amount of fingerprints information stored in systems has been rising sharply, making it challenging to process and store fingerprints efficiently and robustly with traditional standalone systems and relational databases. In this paper, we propose a scalable distributed fingerprint identification system, named DFIS. It combines the feature extraction procedure with HIPI library and optimizes the load balance strategy of MongoDB to construct a much more robust and stable system. Related experiments and simulations have been carried out and results show that DFIS can reduce the time expense by 70% during the features extraction procedural. For load balance of MongoDB, DFIS can decrease the difference of access load to less than 5% and meanwhile decrease 50% data migration to gain more reasonable distribution of operation load and data load among shards compared with the default load balance strategy in MongoDB. © Springer international Publishing Switzerland 2015.

关键词： Distributed computer systems

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