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JParEnt: parallel entropy decoding for JPEG decompression on heterogeneous multicore architectures 7

JParEnt: Parallel entropy decoding for JPEG decompression on...

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Euro-Par conference / 7th international Workshop on Programming Models and Applications for Multicores and Manycores (PMAM) held in conjunction with the 21st SIGPLAN Symposium on Principles and Practice of parallel Programming (PPoPP)

作者： Sodsong, Wasuwee Jung, Minyoung Park, Jinwoo Burgstaller, Bernd Yonsei Univ Dept Comp Sci Seoul South Korea

ISBN: (纸本)9781450341967

the JPEG format employs Huffman codes to compress the entropy data of an image. Huffman codewords are of variable length, which makes parallel entropy decoding a difficult problem. To determine the start position of a codeword in the bitstream, the previous codeword must be decoded first. We present JParEnt, a new approach to parallel entropy decoding for JPEG decompression on heterogeneous multicores. JParEnt conducts JPEG decompression in two steps: (1)an efficient sequential scan of the entropy data on the CPU to determine the start-positions (boundaries) of coefficient blocks in the bitstream, followed by (2)a parallel entropy decoding step on the graphics processing unit (GPU). the block boundary scan constitutes a reinterpretation of the Huffman-coded entropy data to determine codeword boundaries in the bitstream. We introduce a dynamic workload partitioning scheme to account for GPUs of low compute power relative to the CPU. this configuration has become common with the advent of SoCs with integrated graphics processors (IGPs). We leverage additional parallelism through pipelined execution across CPU and GPU. For systems providing a unified address space between CPU and GPU, we employ zero-copy to completely eliminate the data transfer overhead. Our experimental evaluation of JParEnt was conducted on six heterogeneous multicore systems: one server and two desktops with dedicated GPUs, one desktop with an IGP, and two embedded systems. For a selection of more than 1000JPEG images, JParEnt outperforms the SIMD-implementation of the libjpeg-turbo library by up to a factor of 4.3x, and the previously fastest JPEG decompression method for heterogeneous multicores by up to a factor of 2.2x. JParEnt's entropy data scan consumes 45% of the entropy decoding time of libjpeg-turbo on average. Given this new ratio for the sequential part of JPEG decompression, JParEnt achieves up to97% of the maximum attainable speedup (95% on average). On the IGP-based desktop platform,

关键词： JPEG decoding entropy decoding prefix codes heterogeneous multicores GPU programming

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Comparison of Power-Efficiency of Asthmatic Wheezing Wearable Sensor architectures 7th

Comparison of Power-Efficiency of Asthmatic Wheezing Wearabl...

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7th EAI international conference on Sensor Systems and Software (S-CUBE)

作者： Oletic, Dinko Bilas, Vedran Univ Zagreb Fac Elect Engn & Comp Unska 3 Zagreb 10000 Croatia

ISBN: (纸本)9783319615639;9783319615622

Power-requirements of a wireless wearable sensor for quantification of asthmatic wheezing in respiratory sounds, a typical symptom of chronic asthma, are analysed. Two converse sensor architectures are compared. One featuring processing-intensive on-board respiratory sound classification, and the other performing communication-intensive signal streaming, employing compressive sensing (CS) encoding for data-rate reduction, with signal reconstruction and classification performed on the peer mobile device. It is shown that lower total sensor power, ranging from 216 to 357 mu W, may be obtained on the sensor streaming the CS encoded signal, operating at the compression rate higher than 2x. Total power-budget of 328 to 428 mu W is shown required in the architecture with on-board processing.

关键词： m-health Body sensor networks Asthmatic wheeze detection Digital signal processing Compressed sensing Power-analysis

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Design and Implementation of A Distributed Complex Event processing System 7

Design and Implementation of A Distributed Complex Event Pro...

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7th international conference on Electronics and Information Engineering (ICEIE)

作者： Li Yan Shang Yanlei Beijing Univ Posts & Telecommun Networking & Switching Lab Beijing Peoples R China

ISBN: (数字)9781510610811

ISBN: (纸本)9781510610811

Making use of the massive events from event sources such as sensors and bank transactions and extract valuable information is of significant importance. Complex Event processing (CEP), a method of detecting complex events from simple events stream, provides a solution of processing data in real time fast and efficiently. However, a single node CEP system can't satisfy requirements of processing massive event streams from multitudinous event sources. therefore, this article designs a distributed CEP system, which combine Siddhi, a CEP engine, and Storm, a distributed real time computation architecture. this system can construct topology automatically based on the event streams and execution plans provided by users and process the event streams parallel. Compared with single node complex event system, the distributed system can achieve better performance.

关键词： Complex Event processing Distributed Computation Storm

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GPU-Based Gray-Level Co-occurrence Matrix for Extracting Features from Magnetic Resonance images 14

GPU-Based Gray-Level Co-occurrence Matrix for Extracting Fea...

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14th international Symposium on Pervasive Systems, algorithms and Networks (I-SPAN) / 11th international conference on Frontier of Computer Science and Technology (FCST) / 3rd international Symposium of Creative Computing (ISCC)

作者： Tsai, Hsin-Yi Zhang Hanyu Hung, Che-Lun Chen, Hsian-Min Providence Univ Dept Comp Sci & Informat Engn 200Sec 7Taiwan Blvd Taichung 43301 Taiwan Ecole Cent Supelec Lab Math & Informat Complexite & Syst F-92290 Chatenay Malabry France Providence Univ Dept Comp Sci & Commun Engn 200Sec 7Taiwan Blvd Taichung 43301 Taiwan Providence Univ Big Data Res Ctr 200Sec 7Taiwan Blvd Taichung 43301 Taiwan Taichung Vet Gen Hosp Dept Med Res 1650Sec 4Taiwan Blvd Taichung 40705 Taiwan

ISBN: (纸本)9781538608401

With the continuously increasing power of computation, especially in the region of parallel computing, computer-based texture analysis, computer-assisted classification methods, automated pathology detections, etc. are more and more commonly performed on medical images, like X-ray, Magnetic Resonance (MR) images, for clinical or scientific purposes. these procedures almost always include a stage of textural feature extraction, which usually requires an extensive computation. In this paper, we propose a GPGPU (General-purpose computing on graphics processing units)-based parallel method to accelerate the extraction of a set of features based on the Gray-Level Co-Occurrence Matrix (GLCM) which is a second order statistic that characterizes textures. Performance evaluation of the proposed method implemented with CUDA C is carried out on various GPU devices by comparing to its serial counterpart which is implemented in both Matlab and C on a single node. A series of experimental tests focused on Magnetic Resonance (MR) brain images demonstrate that the proposed method is very efficient and superior to the serial counterpart. A speedup of about 30 - 100 fold is achieved in general.

关键词： Magnetic Resonance Imaging (MRI) Gray-Level Co-occurrence Matrix Texture Features Extraction GPGPU

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A Comparative Review Of Data Warehousing ETL Tools With New Trends And Industry Insight 7

A Comparative Review Of Data Warehousing ETL Tools With New ...

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7th IEEE international Advance Computing conference (IACC)

作者： Mukherjee, Rajendrani Kar, Pragma Calcutta Inst Engn & Management Informat Technol Kolkata India Jadavpur Univ Sch Educ Technol Kolkata India

ISBN: (纸本)9781509015603

Data Warehouse is a repository of strategic data from many sources gathered over a long period of time. Traditional DW operations mainly comprise of extracting data from multiple sources, transforming these data into a compatible form and finally loading them to DW schema for further analysis. the extract-transform-load (ETL) functions need to be incorporated into appropriate tools so that organisations can utilise these tools efficiently as required. there is a wide variety of such tools available in market. In this paper, we have compared different aspects of some popular ETL tools (Informatica, Datastage, Ab Initio, Oracle Data Integrator, SSIS) and have analyzed their advantages and disadvantages. We have also highlighted some salient features (performance optimisation, data lineage, real time data analysis, cost, language binding etc) of these tools and represented them with a comparative study. Apart from the review of the ETL tools, the paper also provides feedback from data science industry which narrates the market value and relevance of the tools in practical scenario. However, the traditional DW concept is expanding rapidly with the advent of big data, cloud computing, real time data analysis and the growing need of parsing information from structured and unstructured data sources. In this paper, we have also identified these factors which are transforming the definition of data warehousing.

关键词： Transformation Data Warehouse ETL tools OLAP parallel processing

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7th international conference on Mathematical Methods, Models and architectures for Computer Network Security, MMM-ACNS 2017

7th International Conference on Mathematical Methods, Models...

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7th international conference on Mathematical Methods, Models and architectures for Computer Network Security, MMM-ACNS 2017

ISBN: (纸本)9783319651262

the proceedings contain 28papers. the special focus in this conference is on Mathematical Methods, Models and architectures for Computer Network Security. the topics include: Meeting requirements imposed by secure software development standards and still remaining agile;adapting enterprise security approaches for evolving cloud processing and networking models;data mining and information security;extending FAST-CPS for the analysis of data flows in cyber-physical systems;visualization-driven approach to anomaly detection in the movement of critical infrastructure;detection and mitigation of time delay injection attacks on industrial control systems with PLCs;choosing models for security metrics visualization;a visual high interaction web crawler;race condition faults in multi-core systems;security requirements for the deployment of services across tactical SOA;nodal cooperation equilibrium analysis in multi-hop wireless ad hoc networks with a reputation system;network anomaly detection based on an ensemble of adaptive binary classifiers;cardholder’s reputation system for contextual risk management in payment transactions;towards self-aware approach for mobile devices security;resident security system for government;a system enabling malware clustering based on suspicious activity trees;malware analysis and detection via activity trees in user-dependent environment;a concept of clustering-based method for botnet detection;easy 4G/LTE IMSI catchers for non-programmers;anomaly detection in cognitive radio networks exploiting singular spectrum analysis;highly efficient privacy preserving authentication for ITS;automated cryptographic analysis of the pedersen commitment scheme and steganalysis based on statistical properties of the encrypted messages.

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Low-power parallel data processing using computation reuse 2017

Low-power parallel data processing using computation reuse

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7th international conference on Information Communication and Management, ICICM 2017

作者： Dabiri, Bita Hossein, Seyyed Rezaei, Seyyed Aghaei Modarressi, Mehdi Department of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Iran

ISBN: (纸本)9781450352796

A wide range of real-world applications, including DSP, deep learning, multimedia, and scientific algorithms generally include fixed-point and floating-point arithmetic operations and trigonometric functions which have long latency and high power usage. In this paper, we propose a computation reuse mechanism for multicore processors that reuses the results of an arithmetic operation for subsequent operations with (approximately) the same operands. It adds a small so-called result cache to every functional unit that keeps a few recent operands and their results to detect repetitive operands and reuse the results. Taking advantage of the value locality inherent in many real-world applications, our architecture relies on a multi-stage interconnection network to distribute input data elements across the cores of a multi-core processor in such a way that the data locality of each core is increased. this way, each core has higher computation reuse rate that translates to more power consumption reduction. Experimental results show that the proposed mechanism increases the result cache hit rate, which leads to a significant reduction in power consumption of arithmetic operations. © 2017 Association for Computing Machinery.

关键词： Electric power utilization

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Construction of performance model of tile CAQR and performance result of the implementation 11

Construction of performance model of tile CAQR and performan...

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11th IEEE international Symposium on Embedded Multicore/Many-Core Systems-on-Chip (MCSoC)

作者： Takayanagi, Masatoshi Suzuki, Tomohiro Univ Yamanashi 4-3-11 Takeda Kofu Yamanashi 4008511 Japan RIKEN Adv Inst Computat Sci Chuo Ku 7-1-26 Minatojima Minami Machi Kobe Hyogo 6500047 Japan

ISBN: (纸本)9781538634417

Highly parallel computational resources can be exploited by asynchronously executing many fine-grained tasks. the tile algorithm for matrix decomposition can generate many fine-grained tasks, so is suitable for modern multicore/manycore architectures. However, the performance of this algorithm significantly depends on the tile size. We implement the tile algorithm in OpenMP/MPI hybrid fashion on a cluster system and construct a performance model that tunes the tile size by measuring the performance of simple computational kernels in our implementation. In this report, we test our communication-avoiding tile QR implementation for tall and skinny matrices on the K computer, and demonstrate the applicability of the performance model.

关键词： Matrix decomposition Kernel Task analysis Clustering algorithms Multicore processing Dynamic scheduling Computational modeling matrix decomposition task analysis PERFORMANCE MODELING dynamic scheduling Clustering algorithms Tile Computational modeling Kernel Seeds

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Fast digital simulation of SAR echoes based on GPU 2017

Fast digital simulation of SAR echoes based on GPU

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7th international conference on Information Communication and Management, ICICM 2017

作者： Zhu, Mingbo Chen, Qi Guo, Tao Dong, Wei Department of Electronics and Information Engineering Naval Aeronautical and Astronautical University Yantai China Equipment and Technique Office Naval Air Traffic Control Center Beijing China

ISBN: (纸本)9781450352796

To deal with the fast simulation of Synthetic Aperture Radar (SAR) echoes, in this paper, we introduce an fast digital simulation method based on Graphic processing Unit (GPU). Model of SAR echoes is established at first. then, the digital simulation for SAR echo of single pulse is optimized by improved concentric circle algorithm. Moreover, the parallel computation based on GPU is adopted to further accelerate the whole digital simulation of all the SAR echoes. In the end, the validity of the above fast digital simulation method of SAR echoes has been verified and the experimental results show that the above method can accelerate the simulation speed dramatically compared with the traditional one. © 2017 Association for Computing Machinery.

关键词： Graphics processing unit

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Computing Framework of Large-Scale Dilated Polyhedral DEM Particles Simulation Based on GPU 7th

Computing Framework of Large-Scale Dilated Polyhedral DEM Pa...

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7th international conference on Discrete Element Methods (DEM)

作者： Zhang, Chi Wang, Yuxin Wang, Yulong Liu, Lu Ji, Shunying Guo, He Dalian Univ Technol Sch Comp Sci & Technol Dalian Peoples R China

ISBN: (纸本)9789811019265;9789811019258

Dilated polyhedral element can accurately construct geometric shape of irregular particles, which can improve the accuracy of contact-impact computing remarkably. But the data structure of dilated polyhedral is more complex than sphere's, and there are always a huge amount of DEM particles need to be considered, so the calculation burden is heavy, and the computation process is very time-consuming. It has great practical significance to implement a computing framework of dilated polyhedral DEM particles simulation with high efficiency. this framework completes parallel computing acceleration of large-scale dilated polyhedral particles based on GPU by using CUDA. Loose coupling among different parts of computing framework enable it to support different mechanical models. From the perspective of user and adequate consideration of the characteristics of DEM calculation, UI interface which is implemented under QT platform is designed elaborately. OpenGL is used for visualization of calculation results. Tests of multiple sets of data show that this framework can effectively simulate and display scenarios of complex particles contact-impact process dynamically.

关键词： Graphics processing unit

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