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8th ieee International symposium on Embedded Computing and System Design (ISED)

作者： Chakraborty, Anirban Banerjee, Ayan Indian Inst Engn Sci & Technol Dept Elect & Telecommun Engn Sibpur Howrah India

ISBN: (纸本)9781538665756

there is a dearth of high quality reconfigurable hardware for DWT which can be extensively used in various real time signal and image processing applications. In this article, we have focused on proposing a dedicated customizable hardware for DWT applicable to 1D/2D signal processing. We have proposed bit-serial distributed Arithmetic (DA) based VLSI architectures for 1D/2D DWT. Exploitation of DA enables us to make our designs Multiplierless, thereby consuming less area. Bit serial configuration of DA is also exploited to introduce modularity and pipelining in the proposed convolution DWT based 1D/2D architectures. though the speed of the proposed designs may not be suitable for certain applications, a number of parallel channels can be introduced for the same. the provision of mode selection can efficiently be used to realize 9/7 and also 5/3 DWT filters in the same proposed architecture. In the proposed 1D/2D architecture, we have achieved about 50% memory size reduction, 30% reduction in area consumption and comparable speed in comparison to the other latest notable DWT architecture so far. We have verified the viability of our proposed 2D architecture by utilizing it in real time image decomposition.

关键词： DWT distributed arithmetic multiplierless image decomposition image enhancement

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NDN Producer Mobility Management based on Echo State Network: a Lightweight Machine Learning Approach 24

NDN Producer Mobility Management based on Echo State Network...

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24th ieee International Conference on parallel and distributed Systems (ICPADS)

作者： Li, Yu Piao, Xuewei Zhang, Haijun Lei, Kai Peking Univ Sch Elect & Comp Engn SECE Shenzhen Key Lab Informat Centr Networking & Bloc Shenzhen 518055 Peoples R China Univ Sci & Technol Beijing Beijing Peoples R China

ISBN: (纸本)9781538673089

NDN is one of promising underlying network architectures that supporting 5G because of its characteristics such as decoupling senders and receivers, hop by hop transmission, in network caching, etc. However, it still faces challenges in producer mobility management like the triangle routing problem (non optimal routing path) and global centralization of the home agent, causing a poor scalability in large network scales and long handover delay. In this paper, we propose the ESN-PBA, a NDN producer mobility management scheme using the ESN in prediction to realize a lightweight machine learning based seamless handover algorithm. Better than the existing fixed and post-adjustment management schemes of producer mobility management, the ESN-PBA can perceive nodes movements heuristically and pre-configure the adjustment in advance to reduce overall processing overhead. In addition, with fine-grained home router status feedbacks and NDN content data oriented philosophy, the training process of normal machine learning method can be mutually enhanced. the experimental results in ndnSIM show that, in the case of successful prediction, the effect of seamless handover can be achieved straightly on the fly. In order to improve the hit rate of cache, we take advantage of NDN's multipath forwarding support, the utilization of ESN prediction of multiple candidates and synchronous forwarding. Compared with PIT-based approach and DNS-based approach, the handover delay of ESN-PBA reduces by 66.7% and 75% respectively. Besides, its handover overhead reduces by 38.4%, compared with DNS-based approach.

关键词： Named Data Networking Producer Mobility 5G Heterogeneous Network Echo State Network Movement Prediction Model

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Low-Complexity Generator Polynomial Search for Turbo Trellis-Coded Spatial Modulation Using Symbol-based EXIT Charts 10

Low-Complexity Generator Polynomial Search for Turbo Trellis...

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10th ieee International symposium on Turbo Codes & Iterative Information processing (ISTC)

作者： Hara, Takanori Ishibashi, Koji Ng, Soon Xin Hanzo, Lajos Univ Electrocommun Adv Wireless & Commun Res Ctr AWCC 1-5-1 Chofugaoka Chofu Tokyo 1828585 Japan Univ Southampton Sch Elect & Comp Sci Southampton SO17 1BJ Hants England

ISBN: (纸本)9781538670484

A low-complexity generator polynomial (GP) search method is proposed for spatial modulation relying on turbo trellis coding (SM-TTC), which achieves a high coding gain over independent and identically distributed (i.i.d.) fading channels and is robust against spatial correlation among receiving antenna elements. the proposed GP search method invokes symbol-based extrinsic information transfer (EXIT) charts and does not need to execute iterative decoding. It is demonstrated that our SMTTC scheme with the best GP obtained by the proposed method outperforms one with conventional codes.

关键词： Modulation Correlation Linear antenna arrays Iterative decoding Transmitters Search methods

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Serverless Skeletons for Elastic parallel processing

Serverless Skeletons for Elastic Parallel Processing

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Big Data Intelligence and Computing (DATACOM), International Conference on

作者： Stefan Kehrer Jochen Scheffold Wolfgang Blochinger Parallel and Distributed Computing Group Reutlingen University Germany

ISBN: (数字)9781728141176

ISBN: (纸本)9781728141183

Serverless computing is an emerging cloud computing paradigm with the goal of freeing developers from resource management issues. As of today, serverless computing platforms are mainly used to process computations triggered by events or user requests that can be executed independently of each other. these workloads benefit from on-demand and elastic compute resources as well as per-function billing. However, it is still an open research question to which extent parallel applications, which comprise most often complex coordination and communication patterns, can benefit from serverless *** this paper, we introduce serverless skeletons for parallel cloud programming to free developers from both parallelism and resource management issues. In particular, we investigate on the well-known and widely used farm skeleton, which supports the implementation of a wide range of applications. To evaluate our concepts, we present a prototypical development and runtime framework and implement two applications based on our frame-work: Numerical integration and hyperparameter optimization - a commonly applied technique in machine learning. We report on performance measurements for both applications and discuss the usefulness of our approach.

关键词： Measurement Runtime Serverless computing parallel processing Programming Hyperparameter optimization Skeleton

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A Computational Evaluation of distributed Machine Learning Algorithms

A Computational Evaluation of Distributed Machine Learning A...

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International Conference for Convergence of Technology (I2CT)

作者： Junaid Magdum Ritesh Ghorse Chetan Chaku Rahul Barhate Shyam Deshmukh Department of Information Technology PICT Pune India Department of Information Technology MIT College of Engineering Pune India

ISBN: (数字)9781538680759

ISBN: (纸本)9781538680766

Over the past few years, availability of data throughout the internet has scaled to petabytes. processing this data demands a strong computing mechanism rather than usual machine learning techniques. distributed machine learning solves this problem with distributed system environment. It refers to multi-node machine learning algorithms and systems that are designed to scale to larger input data sizes. To understand the best possible utilization for each algorithm in a parallel computing environment, a detailed study of these distributed machine learning algorithms is necessary. To summarize and evaluate their performance, parameters such as Execution time, CPU usage, Memory usage rate and Accuracy have been considered for each algorithm. the experiment conducted on LightGBM, CatBoost, AdaBoost and XGBoost demonstrated that CatBoost performed the best with an accuracy of 81.31% amongst the other algorithms. this analysis will thus help beginners and business firms chose the appropriate algorithm for their specific distributed machine learning application.

关键词： Machine learning algorithms Boosting Training Decision trees Data models Classification algorithms

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proceedings - 15th ieee International Conference on Trust, Security and Privacy in Computing and Communications, 10th ieee International Conference on Big Data Science and Engineering and 14th ieee International symposium on parallel and distributed processing with Applications, ieee TrustCom/BigDataSE/ISPA 2016

Proceedings - 15th IEEE International Conference on Trust, S...

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Joint 15th ieee International Conference on Trust, Security and Privacy in Computing and Communications, 10th ieee International Conference on Big Data Science and Engineering and 14th ieee International symposium on parallel and distributed processing with Applications, ieee TrustCom/BigDataSE/ISPA 2016

ISBN: (纸本)9781509032051

the proceedings contain 311 papers. the topics discussed include: a robust image hashing with enhanced randomness by using random walk on zigzag blocking;securing fast learning! ridge regression over encrypted big data;computational trust model for repeated trust games;formal analysis of selective disclosure attribute-based credential system in applied Pi calculus;node trust prediction framework in mobile ad hoc networks;trust enhancement over range search for encrypted data;healthcare fraud detection based on trustworthiness of doctors;integrated security for services hosted in virtual environments;a permissioned blockchain framework for supporting instant transaction and dynamic block size;trust validation of cloud IaaS: a customer-centric approach;distributed bitcoin account management;trusted Boolean search on cloud using searchable symmetric encryption;and dynamic attribute-based access control in cloud storage systems.

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Evaluating Student Engagement towards Integrating parallel and distributed Computing (PDC) Topics in Undergraduate Level Computer Science Curriculum 19

Evaluating Student Engagement towards Integrating Parallel a...

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proceedings of the 50th ACM Technical symposium on Computer Science Education

作者： Mary Smith Srishti Srivastava Hawaii Pacific University Honolulu HI USA University of Southern Indiana Evansville IN USA

ISBN: (纸本)9781450358903

this research is a cross university study of evaluating whether there are differences between demographic factors (gender, age, class standing) and student engagement via unplugged activities introducing parallel and distributed computing (PDC) topics in CS1, CS2, and CS3 level courses in an undergraduate computer science (CS) curriculum. the collaboration stemmed from attending a NSF Center for parallel and distributed Computing Curriculum Development and Educational Resources (CDER) PDC Curriculum Early Adopter Grant and Summer Training Program. Initiatives by the National Science Foundation in conjunction with the Institute for Electronic and Electrical Engineers' Technical Committee of parallel processing (NSF/ieee-TCPP) encourage and promote the introduction of PDC concepts in the early CS undergraduate courses. the researchers used the [Wiggins, 2017: Assessing Student Perspective of Engagement in Class (ASPECT)] survey to collect data from ~105 undergraduate CS students after each unplugged activity. Demographic data (gender, age, class standing) was added to the survey to determine if there are differences in these and student engagement. For the study, the researchers designed two unplugged activities to demonstrate the fundamental concepts of PDC. the first activity help students learn the key benefits of parallel computing, and the limitations imposed by Amdahl's and Gustafson's law. the second activity exhibits the concepts of scheduling and load balancing. Our findings indicate there are no significant differences between gender, age, class standing and student engagement. the researchers plan to continue their research on unplugged activities and student engagement. Additional activities will be developed to introduce other PDC topics.

关键词： student engagement parallel and distributed computing education unplugged activity active learning

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A High-Level C++ Approach to Manage Local Errors, Asynchrony and Faults in an MPI Application 26

A High-Level C++ Approach to Manage Local Errors, Asynchrony...

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26th Euromicro International Conference on parallel, distributed, and Network-Based processing, PDP 2018

作者： Engwer, Christian Altenbernd, Mirco Dreier, Nils-Arne Goddeke, Dominik Applied Mathematics University of Munster Orleansring 10 Munster48149 Germany IANS University of Stuttgart Allmandring 5b Stuttgart70569 Germany

ISBN: (纸本)9781538649756

C++ advocates exceptions as the preferred way to handle unexpected behaviour of an implementation in the code. this does not integrate well with the error handling of MPI, which more or less always results in program termination in case of MPI failures. In particular, a local C++ exception can currently lead to a deadlock due to unfinished communication requests on remote hosts. At the same time, future MPI implementations are expected to include an API to continue computations even after a hard fault (node loss), i.e. the worst possible unexpected behaviour. In this paper we present an approach that adds extended exception propagation support to C++ MPI programs. Our technique allows to propagate local exceptions to remote hosts to avoid deadlocks, and to map MPI failures on remote hosts to local exceptions. A use case of particular interest are asynchronous 'local failure local recovery' resilience approaches. Our prototype implementation uses MPI-3.0 features only. In addition we present a dedicated implementation, which integrates seamlessly with MPI-ULFM, i.e. the most prominent proposal for extending MPI towards fault tolerance. Our implementation is available at https://***/christi/test-mpi-exceptions. © 2018 ieee.

关键词： Fault tolerance

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Effects of the Random Distributions on the Laminar Flow and Heat Transfer in a Quasi-Counter Flow parallel-Plate Membrane Channel

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HEAT TRANSFER ENGINEERING 2018年第17-18期39卷 1520-1527页

作者： Huang, Si-Min Qiu, Dong Ye, Wei-Biao Hong, Yuxiang Huang, Weihao Yang, Minlin Dongguan Univ Technol Key Lab Distributed Energy Syst Guangdong Prov Dongguan 523808 Peoples R China Xiangtan Univ Sch Mech Engn Dept Proc Equipment & Control Engn Xiangtan Peoples R China Lishui Univ Dept Chem & Chem Engn Lishui Zhejiang Peoples R China

An internally cooled parallel-plate membrane contactor has been employed for liquid desiccant air dehumidification. the contactor is comprised of a series of quasi-counter flow parallel-plate membrane channels (QCPMC). the processing air and the liquid desiccant (solution) streams are separated by the membranes. Cooling tubes are installed in the solution channel to take away the absorption heat. the laminar flow and heat transfer in the QCPMC with the cooling tubes in the solution side (QCPMCC) are studied based on a unit cell containing the sandwiched domain outside the cooling tubes between two neighboring membranes. this paper is focused on the effects of the random distributions in the height direction on the transport phenomena in the QCPMCC. the governing equations of the momentum and thermal transports are built up together with a uniform wall temperature boundary condition. the product of the mean friction factor and Reynolds number and the mean Nusselt number are then calculated. Effects of the various random distributions in the height direction on the product of the mean friction factor and Reynolds number and the mean Nusselt number are analyzed. Compared to the regular arrangement, the mean Nusselt number for the random distribution is larger than that for the regular one when the Reynolds number is less than 68.5. However when the Reynolds number is larger than 68.5, the mean Nusselt number for the random distribution is smaller than that for the regular one.

关键词： Reynolds number

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Scalable Concurrency Debugging with distributed Graph processing 2018

Scalable Concurrency Debugging with Distributed Graph Proces...

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16th International symposium on Code Generation and Optimization (CGO)

作者： Zheng, Long Liao, Xiaofei Jin, Hai Zhao, Jieshan Wang, Qinggang Huazhong Univ Sci & Technol Serv Comp Technol & Syst Lab Big Data Technol & Syst Lab Cluster & Grid Comp Lab Wuhan 430074 Hubei Peoples R China

ISBN: (纸本)9781450356176

Existing constraint-solving-based technique enables an efficient and high-coverage concurrency debugging. Yet, there remains a significant gap between the state of the art and the state of the programming practices for scaling to handle long-running execution of programs. In this paper, we revisit the scalability problem of state-of-the-art constraint-solving-based technique. Our key insight is that concurrency debugging for many real-world concurrency bugs can be turned into a graph traversal problem. We therefore present GraphDebugger, a novel debugging framework to enable the scalable concurrency analysis on program graphs via a tailored graph-parallel analysis in a distributed environment. It is verified that GraphDebugger is more capable than CLAP in reproducing the real-world bugs that involve a complex concurrency analysis. Our extensive evaluation on 7 real-world programs shows that, GraphDebugger (deployed on an 8-node EC2 like cluster) is significantly efficient to reproduce concurrency bugs within 1 similar to 8 minutes while CLAP does so with 1 similar to 30 hours, or even fails to return the solutions.

关键词： concurrency debugging graph processing scalability multi-threaded programs

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