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检索条件"任意字段=10th International Conference on Algorithms and Architectures for Parallel Processing"

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Proceedings of the international conference on parallel processing Workshops

Proceedings of the International Conference on Parallel Proc...

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44th Annual conference of the international conference on parallel processing Workshops, ICPPW 2015

ISBN: (纸本)9781467375894

the proceedings contain 35 papers. the topics discussed include: side effect mitigation algorithm for cache maintenance in opportunistic networks;simple floor plan construction via cloudsourcing;using open edX forum for supporting collaborative learning;towards an automatic prediction of image processing algorithms performances on embedded heterogeneous architectures;multi-core approach towards efficient biometric cryptosystems;sparse matrix sparse vector multiplication - a novel approach;thread-level value speculation for image-processing applications;a special sorting method for neighbor search procedure in smoothed particle hydrodynamics on GPUs;the design and implementation of embedded online laboratory;and spatial join query processing in cloud: analyzing design choices and performance comparisons.

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parallel Applications and On-chip Traffic Distributions: Observation, Implication and Modelling 10

Parallel Applications and On-chip Traffic Distributions: Obs...

引用

10th international conference on Software Technologies (ICSOFT)

作者： Xu, thomas Canhao Pohjankukka, Jonne Nevalainen, Paavo Pahikkala, Tapio Leppanen, Ville Univ Turku Dept Informat Technol Joukahaisenkatu 3-5 B FIN-20520 Turku Finland

ISBN: (纸本)9789897581397

We study the traffic characteristics of parallel and high performance computing applications in this paper. Applications that utilize multiple cores are more and more common nowadays due to the emergence of multicore processors. However the design nature of single-threaded applications and multi-threaded applications can vary significantly. Furthermore the on-chip communication profile of multicore systems should be analysed and modelled for characterization and simulation purposes. We investigate several applications running on a full system simulation environment. the on-chip communication traces are gathered and analysed. We study the detailed low-level profiles of these applications. the applications are categorized into different groups according to various parallel programming paradigms. We discover that the trace data follow different parameters of power-law model. the problem is solved by applying least-squares linear regression. We propose a generic synthetic traffic model based on the analysis results.

关键词： Distributed architectures parallel Computing High Performance Computing Communication Networks Performance Evaluation Multicore Systems

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Efficient Lava Flows Simulations with OpenCL: A preliminary application for Civil Defence Purposes 10

Efficient Lava Flows Simulations with OpenCL: A preliminary ...

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10th international conference on P2P, parallel, Grid, Cloud and Internet Computing 3PGCIC

作者： De Rango, A. Macri, M. Spataro, D. D'Ambrosio, D. Spataro, W. Univ Calabria Dept Math & Comp Sci I-87030 Commenda Di Rende Italy CNR IRPI Sez Cosenza Cosenza Italy

ISBN: (纸本)9781467394734

GPGPU (General Purpose computing on Graphics processing Units) has marked a revolution in the field of parallel Computing allowing to achieve computational performance unimaginable until a few years ago. this hardware has proven to be extremely reliable and suitable to simulate Cellular Automata (CA) models for modeling complex systems whose evolution can be described in terms of local interactions. Starting from previous GPGPU implementations of CA models with CUDA, this paper presents an effective implementation of a well-known numerical model for simulating lava flows on Graphical processing Units (GPU) based on the OpenCL (Open Computing Language) standard. In addition, a preliminary Civil Defence application related Hazard maps of an area located at Mt. Etna volcano (South Italy), confirms the validity of OpenCL and both low-cost and high-end graphics hardware as an alternative to expensive solutions for the simulation of CA models.

关键词： GPGPU OpenCL Cellular Automata parallel Software Tools Hazard Maps Modeling and Simulation

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Custom FPGA-based Soft-Processors for Sparse Graph Acceleration 26

Custom FPGA-based Soft-Processors for Sparse Graph Accelerat...

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26th international conference on Application-Specific Systems, architectures and Processors (ASAP)

作者： Kapre, Nachiket Nanyang Technol Univ Sch Comp Engn Singapore Singapore

ISBN: (纸本)9781479919253

FPGA-based soft processors customized for operations on sparse graphs can deliver significant performance improvements over conventional organizations (ARMv7 CPUs) for bulk synchronous sparse graph algorithms. We develop a stripped-down soft processor ISA to implement specific repetitive operations on graph nodes and edges that are commonly observed in sparse graph computations. In the processing core, we provide hardware support for rapidly fetching and processing state of local graph nodes and edges through spatial address generators and zero-overhead loop iterators. We interconnect a 2D array of these lightweight processors with a packet-switched network-on-chip to enable fine-grained operand routing along the graph edges and provide custom send/receive instructions in the soft processor. We develop the processor RTL using Vivado High-Level Synthesis and also provide an assembler and compilation flow to configure the processor instruction and data memories. We outperform a Microblaze (100MHz on Zedboard) and an NIOS-II/f (100MHz on DE2-115) by 6x (single processor design) as well as the ARMv7 dual-core CPU on the Zynq SoCs by as much as 10x on the Xilinx ZC706 board (100 processor design) across a range of matrix datasets.

关键词： PROCESSOR Line graph address generator Assemblers Customs Graph algorithms performance boost Customization central processing units

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Stateful complex event detection on event streams using parallelization of event stream aggregations and detection tasks 16

Stateful complex event detection on event streams using para...

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Proceedings of the 10th ACM international conference on Distributed and Event-based Systems

作者： Saeed Fathollahzadeh Kia Teymourian Mohsen Sharifi Iran University of Science and Technology Rice University

ISBN: (纸本)9781450340212

Detection of stateful complex event patterns using parallel programming features is a challenging task because of statefulness of event detection operators. parallelization of event detection tasks needs to be implemented in a way that keeps track of state changes by new arriving *** this paper, we describe our implementation for a customized complex event detection engine by using Open Multi-processing (OpenMP), a shared memory programming model. In our system event detection is implemented using Deterministic Finite Automata (DFAs). We implemented a data stream aggregator that merges 4 given event streams into a sequence of C++ objects in a buffer used as source event stream for event detection in a next processing step. We describe implementation details and 3 architectural variations for stream aggregation and parallelized of event processing. We conducted performance experiments with each of the variations and report some of our experimental results. A comparison of our performance results shows that for event processing on single machine with multi cores and limited memory, using mutli-threads with shared buffer has better stream processing performance than an implementation with multi-processes and shared memory.

关键词： event detection data streams complex event processing

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Performance Evaluation of a MapReduce Hadoop-based Implementation for processing Large Virtual Campus Log Files 10

Performance Evaluation of a MapReduce Hadoop-based Implement...

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10th international conference on P2P, parallel, Grid, Cloud and Internet Computing 3PGCIC

作者： Xhafa, Fatos Garcia, Daniel Ramirez, Daniel Caballe, Santi Univ Politecn Cataluna Barcelona Spain Open Univ Catalonia Barcelona Spain

ISBN: (纸本)9781467394734

Cloud computing technologies are bringing new scales of computational processing power and storage capacity to meet very demanding requirements of today's applications. One such family of applications is the one of analytics based on processing big data. More specifically, there is a large family of analytics applications from processing log data files. Indeed, log data files are commonplace in many Internet-based systems and applications, comprising system logs, server logs, application logs, databases logs, user activity logs, etc. these applications are analytics oriented applications based on processing the various types of log files. While log data file processing has been recently an issue of investigation by many researchers and developers, the new feature is that of scale: Cloud based systems can enable processing unlimited amount of data either off-line or online in streaming mode. In this work we evaluate the performance of a MapReduce Hadoop-based implementation for processing large log data files of a Virtual Campus. the study aims to reveal the potential of using such implementations as a basis for learning analytics for use by a variety of users in a Virtual Campus.

关键词： Big Data Massive processing Learning Analytics Mining Performance Virtual Campus Log Files MapReduce Hadoop Cloud Computing

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Spatial Data processing with MapReduce 10

Spatial Data Processing with MapReduce

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10th IEEE international conference on Industrial and Information Systems (ICIIS)

作者： Gunawardena, Tilani Vicari, Annamaria Mecca, Giansalvatore Univ Basilicata Dept Math Comp Sci & Econ Potenza Italy Natl Inst Geophys & Volcanol Rome Italy

ISBN: (纸本)9781479918768

the current development of high performance parallel supercomputing infrastructures are pushing the boundaries of applications of science and are bringing new paradigms into engineering practices and simulations. Earthquake engineering is also one of the major fields, which benefits from above by looking for solutions in grid computing and cloud computing techniques. Generally, earthquake simulations involve analysis of petabytes of data. Analyzing these large amounts of data in parallel in thousands of nodes in computer clusters results in gaining high performances. Open source cloud solutions such as Hadoop Map Reduce, which is highly scalable and capable of processing large amount of data rapidly in parallel on large clusters provide better solution compared to RDBDM. Both GPUs and MapReduce are designed to support vast data parallelism. For performance considerations, GPU computing could be adopted over low performing CPU systems. this paper discusses MapReduce system using Hadoop and Mars. Mars is a MapReduce framework on graphics processor. Hence, the proposition is to use GPU based systems for earthquake simulations in which Digital elevation model 3D data sets are fully materialized where scientist can make use of these data for various analysis and simulations.

关键词： MapReduce Spatial Data GPU computing CUDA Hadoop Big Data

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Improving parallel processing of Matrix-Based Similarity Measures on Modern GPUs 8th

Improving Parallel Processing of Matrix-Based Similarity Mea...

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8th international conference on Similarity Search and Applications (SISAP)

作者： Krulis, Martin Bednarek, David Brabec, Michal Charles Univ Prague Fac Math & Phys Parallel Architectures Algorithms Applicat Res Gr Malostranske Nam 25 Prague Czech Republic

ISBN: (纸本)9783319250878;9783319250861

Dynamic programming techniques are well-established and employed by various practical algorithms which are used as similarity measures, for instance the edit-distance algorithm or the dynamic time warping algorithm. these algorithms usually operate in iteration-based fashion where new values are computed from values of the previous iteration, thus they cannot be processed by simple data-parallel approaches. In this paper, we propose a way how to utilize computational power of massively parallel GPUs to compute dynamic programming algorithms effectively and efficiently. We address both the problem of computing one distance on large inputs concurrently and the problem of computing large number of distances simultaneously (e.g., when a similarity query is being resolved).

关键词： GPU CUDA Dynamic programming Edit distance Dynamic time warping

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An Escrow-Free Hierarchical Identity-Based Signature Model for Cloud Storage 15th

An Escrow-Free Hierarchical Identity-Based Signature Model f...

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15th international conference on algorithms and architectures for parallel processing (ICA3PP)

作者： Chen, Peixin Wang, Xiaofeng Su, Jinshu Natl Univ Def Technol Coll Comp Changsha 410073 Hunan Peoples R China Natl Univ Def Technol Natl Key Lab Parallel & Distributed Proc Changsha 410073 Hunan Peoples R China

ISBN: (纸本)9783319271613;9783319271606

Hierarchical identity-based cryptography is an efficient technology to address the security issues in cloud storage. However, the inherent key escrow problem primarily hinders the widespread adoption of this cryptosystem in practice. To address the key escrow problem, this paper proposes an escrow-free hierarchical identity-based signature model, in which a user signs messages with a user-selected secret and PKG signing factor apart from the private key. For proving the full security, we formulate three security games with respect to our signature model. We instantiate the escrow-free model into a specific scheme based on the SHER-IBS scheme and prove that our scheme is secure against adaptive chosen ID and message attacks.

关键词： Cryptanalysis Hierarchical identity-based signature Key escrow Bilinear pairing CDH assumption

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Architecture and Scheduling Method of Cloud Video Surveillance System Based on IoT 15th

Architecture and Scheduling Method of Cloud Video Surveillan...

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15th international conference on algorithms and architectures for parallel processing (ICA3PP)

作者： Wei, Xia Li, Wen-Xiang Ran, Cong Pi, Chun-Chun Ma, Ya-Jie Sheng, Yu-Xia Wuhan Univ Sci & Technol Sch Informat Sci & Engn Wuhan 430081 Peoples R China

ISBN: (纸本)9783319271613;9783319271606

To realize conveniently deployed video surveillance applications, this paper designs a cloud service system employing ubiquitously available IoT nodes. Considering limited capacity of each IoT node, this paper first describes the system architecture and operation procedure for application requests, and introduces the design of scheduler's function and typical video processing algorithms. Further, for decreasing transmission conflicts among video/image processor nodes, this paper proposes a scheduling methods based on Genetic Algorithm to rationally utilize the cooperative IoT nodes. Simulation results show that, compared with common methods such as random scheduling and opportunity-balanced scheduling, this method yields much smaller processing delay and transmission delay, together with higher packet delivery ratio.

关键词： Video surveillance Internet of things Cloud computing Scheduling Transmission conflicts Video processing

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