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IEEE international Conference on Big Data and Cloud Computing (BdCloud)

作者： Feng Jing Ying Jiang Shengbin Chen Xirong Lv Jiayi He State Grid Shanxi Electric Power Company Taiyuan China Xiamen Great Power Geo Information Technology Company Ltd Xiamen China School of Computer and Information Engineering Xiamen University of Technology Xiamen China

With the continuous development of data-centric Internet applications, data management solutions for massive data have gradually become a new research direction in vector map rendering. The introduction of distributed "cloud computing" technology has continuously improved the storage and management of massive data. Supported by a large number of distributed systems, it provides normal services to the outside world, as well as fast data location services. The system has good performance in data storage efficiency, node load balancing and system scalability, and has an efficient data positioning mechanism. The basic idea of the system design draws on the hash algorithm and the consistent hash algorithm, and improves the scalability of the basic algorithm. Through the three-tier layout: front-end server layer, consistent hash layer, data node layer, to maximize the consistency, availability, efficiency and scalability of the system.

关键词： Cloud computing Scalability Layout Memory distributed databases systems architecture Rendering (computer graphics)

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Workshop 17: PAISE parallel AI and systems for the Edge

Workshop 17: PAISE Parallel AI and Systems for the Edge

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IEEE international symposium on parallel and distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Pete Beckman Rajesh Sankaran Mathematics and Computer Science Division Argonne National Laboratory USA

ISBN: (数字)9781728174457

ISBN: (纸本)9781728174570

Applications involving voluminous data but needing low-latency computation and local feedback require that the computing be performed as close to the data source as possible — often at the interface to the physical world. Communication constraints and the need for privacy-preserving approaches also dictate the need for computing at the edge. Given the growth in such application scenarios and the recent advances in algorithms and techniques, machine learning and inference at the edge are unfolding and growing at a rapid pace. In support of these applications, a wide range of hardware (CPUs, GPUs, ASICs) is venturing farther away from the center, closer to the physical world. The resulting diversity in edgecomputing hardware in terms of capabilities, architectures, and programming models poses several new challenges.

关键词： Conferences Hardware distributed databases Computer security Mathematics Computer science distributed processing

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parallel Classification of Spatial Points Into Geographical Regions 18

Parallel Classification of Spatial Points Into Geographical ...

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18th international symposium on parallel and distributed Computing (ISPDC)

作者： Tarmur, Sanver Ozturan, Can Bogazici Univ Computat Sci & Engn Program Istanbul Turkey Bogazici Univ Comp Engn Dept Istanbul Turkey

ISBN: (纸本)9781728138015

The amount of data generated by social media, social networks and distributed platforms such as blockchain, have reached quite high levels. Various data analysis methods could be applied this big data. One of these methods is to classify geo-tagged social network data in order to report geographical area associated with the data. We propose an efficient parallel classification approach and implement a classifier tool which is capable of processing huge amount of data. To test our approach, we collect Twitter data over five densest areas of Turkey. There are important factors affecting the classification performance such as the spatial indexing and the parallelization strategies. Hierarchical Triangular Mesh (HTM) and R-Tree spatial indexes are used for indexing regions. For parallel processing data streams classifier tool is implemented based on Apache Spark and Kafka platforms in order to obtain high scalability. To show effectiveness of our method, we perform tests on Amazon Web Services (AWS) Cloud environment and compare our method against a method which implements HTM on a Microsoft SQL Server. Results show that 1.6 - 4.5 fold speed-up is obtained and Twitter data that is collected over a month can be processed effectively in three hours.

关键词： Indexing Servers Sparks Spatial databases Twitter Spatial indexes

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Power sharing between parallel inverters by using droop control with a secondary control loop 10

Power sharing between parallel inverters by using droop cont...

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IEEE 10th international symposium on Power Electronics for distributed Generation systems (PEDG)

作者： Lei, Li Elgendy, Mohammed Wade, Neal Ethni, Salaheddine Newcastle Univ Sch Engn Newcastle Upon Tyne NE1 7RU Tyne & Wear England

ISBN: (纸本)9781728124551

Analysis of power sharing between parallel grid-connected inverters is a popular topic in the microgrid research area. In this paper, droop control with a secondary control loop is presented for an AC microgrid, to improve the accuracy of power sharing performance between parallel inverters. The secondary control loop calculates the reference active power and reactive power input to P-f/Q-V droop control. The proposed method can be used in microgrids which contain many micro sources and loads variations for both islanding and grid-connected operation modes. A simulation model for a microgrid with three generators is built to test the performance of the proposed control method using MATLAB/SIMULINK platform. Results of the new method are compared with the virtual impedance droop control method to illustrate the advantages of the proposed power-sharing method.

关键词： distributed generation droop control parallel operation of inverters power sharing

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parallel simulation of stochastic reward nets using theatre 21

Parallel simulation of stochastic reward nets using theatre

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Proceedings of the 2021 IEEE/ACM 25th international symposium on distributed Simulation and Real Time Applications

作者： Franco Cicirelli Libero Nigro CNR - National Research Council of Italy Italy University of Calabria Italy

ISBN: (纸本)9781665433266

This work aims at the development of tools for supporting modelling and analysis of timed systems by Stochastic Reward Nets (SRN). In a first approach it was proposed and experimented a formal reduction of SRN over Timed Automata (TA) in the context of the Uppaal popular toolbox. The reduction has the merit to allow both exhaustive model checking of an SRN model, useful for the assessment of qualitative properties (e.g., absence of deadlocks, occurrence of particular event sequences etc.), and quantitative analysis through the statistical model checker, which is based on simulations. However, although Uppaal enabled formal reasoning on the semantics of SRN, its practical usage suffers of scalability problems, that is it can introduce severe limitations in time and space when studying complex models. To cope with this problem, this paper describes a Java implementation of the SRN operational core engine, using the lock-free and efficient Theatre actor system which permits the parallel simulation of large models. The realization can be used for functional property checking on an untimed version of a source SRN model, and quantitative estimation of measurables through simulations. The paper discusses the design and implementation of the core engine of SRN on top of Theatre, together with supported intuitive configuration process of an SRN model, and reports some experimental results using a scalable grid computing model. The experiments confirm Theatre/SRN are capable of exploiting the potential of modern multi-core machines and can deliver good execution performances on large models.

关键词： theatre Java stochastic reward nets actors high-performance computing performability analysis

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Scalability and parallelization of Sequential Processing: Big Data Demands and Information Algebras

Scalability and Parallelization of Sequential Processing: Bi...

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international symposium on Computer Science, Digital Economy and Intelligent systems (CSDEIS)

作者： Golubtsov, Peter Lomonosov Moscow State Univ Moscow Russia Natl Res Univ Higher Sch Econ Moscow Russia Russian Inst Sci & Tech Informat VINITI RAS Moscow Russia

ISBN: (纸本)9783030392161;9783030392154

Procedures of sequential updating of information are important for "big data streams" processing because they avoid accumulating and storing large data sets. As a model of information accumulation, we study the Bayesian updating procedure for linear experiments. Analysis and gradual transformation of the original processing scheme in order to increase its efficiency lead to certain mathematical structures - information spaces. We show that processing can be simplified by introducing a special intermediate form of information representation. Thanks to the rich algebraic properties of the corresponding information space, it allows unifying and increasing the efficiency of the information updating. It also leads to various parallelization options for inherently sequential Bayesian procedure, which are suited for distributed data processing platforms, such as MapReduce. Besides, we will see how certain formalization of the concept of information and its algebraic properties can arise simply from adopting data processing to big data demands. Approaches and concepts developed in the paper allow to increase efficiency and uniformity of data processing and present a systematic approach to transforming sequential processing into parallel.

关键词： Big data streams Sequential Bayesian updating Information spaces Algebra of information distributed processing

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Activity Based Approach for Teaching parallel Computing: An Indian Experience 33

Activity Based Approach for Teaching Parallel Computing: An ...

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33rd IEEE international parallel and distributed Processing symposium (IPDPS)

作者： Chitra, P. Ghafoor, Sheikh. K. Thiagarajar Coll Engn Dept Comp Sci & Engn Madurai Tamil Nadu India Tennessee Technol Univ Dept Comp Sci Cookeville TN USA

ISBN: (纸本)9781538655559

Due to the rapid growth in the multicore and GPU based computing devices, the need to teach parallel computing in CS/CE curriculum has become almost mandatory nowadays. A course on parallel Computing systems (PCS) has been designed to provide an understanding of the fundamental principles and engineering trade-offs involved in designing modern parallel computing systems as well as to teach parallel programming techniques necessary to effectively utilize these machines. An activity based learning approach was adopted for teaching the course and several parallel programming paradigms and technologies such OpenMP, MPI, and CUDA have been covered. This course was offered as a required course to graduate students. This paper describes the implementation of the course at Thiagarajar College of Engineering. Evaluation of the implementation of the course reveals that for students who have not been exposed to parallel and distributed computing, i) activity based learning results in better knowledge gain compared to the traditional approach, ii) learning OpenMP was much easier than MPI or CUDA, iii) some parallel and distributed Computing (PDC) concepts such as false sharing were harder to grasp compared to basic concepts, and iv) it is essential to introduce parallel computing in the undergraduate curriculum.

关键词： parallel processing Graphics processing units Education parallel programming distributed computing

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A Case for Stale Synchronous distributed Model for Declarative Recursive Computation

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THEORY AND PRACTICE OF LOGIC PROGRAMMING 2019年第5-6期19卷 1056-1072页

作者： Das, Ariyam Zaniolo, Carlo Univ Calif Los Angeles Dept Comp Sci Los Angeles CA 90024 USA

A large class of traditional graph and data mining algorithms can be concisely expressed in Datalog, and other Logic-based languages, once aggregates are allowed in recursion. In fact, for most BigData algorithms, the difficult semantic issues raised by the use of non-monotonic aggregates in recursion are solved by Pre-Mappability (PreM), a property that assures that for a program with aggregates in recursion there is an equivalent aggregate-stratified program. In this paper we show that, by bringing together the formal abstract semantics of stratified programs with the efficient operational one of unstratified programs, PreM can also facilitate and improve their parallel execution. We prove that PreM-optimized lock-free and decomposable parallel semi-naive evaluations produce the same results as the single executor programs. Therefore, PreM can be assimilated into the data-parallel computation plans of different distributed systems, irrespective of whether these follow bulk synchronous parallel (BSP) or asynchronous computing models. In addition, we show that non-linear recursive queries can be evaluated using a hybrid stale synchronous parallel (SSP) model on distributed environments. After providing a formal correctness proof for the recursive query evaluation with PreM under this relaxed synchronization model, we present experimental evidence of its benefits.

关键词： Datalog Deductive databases Recursive Query Stale Synchronous parallel Model Bulk Synchronous parallel Model parallel and distributed Computing

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A Container-Based Framework to Facilitate Reproducibility in Employing Stochastic Process Algebra for Modeling parallel Computing systems 33

A Container-Based Framework to Facilitate Reproducibility in...

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33rd IEEE international parallel and distributed Processing symposium (IPDPS)

作者： Sanders, William S. Srivastava, Srishti Banicescu, Ioana Mississippi State Univ Comp Sci & Engn Mississippi State MS 39762 USA Univ Southern Indiana Comp Sci 8600 Univ Blvd Evansville IN 47712 USA

ISBN: (纸本)9781538655559

Scientific applications are increasingly complex and domain specific, and the underlying architectures of the parallel and distributed systems on which they are executed also continue to grow in complexity. As these high performance parallel and distributed computing applications and environments continue to grow both in complexity and computing power, there is an increasing financial cost associated with both the acquisition and maintenance of those systems. Therefore, the ability to model the performance of these applications and systems before and during their development and deployment to guide cost-effective decisions about their resources and configurations is highly important to the designers of those applications and systems. Performance Evaluation Process Algebra (PEPA) is a modeling language and framework for modeling parallel and distributed computing and communication applications and systems, and numerous examples are present in the literature where PEPA has been utilized to model these systems for evaluating or predicting their performance using various metrics, including throughput, utilization, and robustness. Since its development, the PEPA modeling framework has been expanded to model biological systems and networks (Bio-PEPA), and massive (on the order of similar to 10(129) components) homogeneous systems with Grouped PEPA (GPEPA). PEPA and its derivatives are implemented in a variety of ways, ranging from plug-ins integrated with the Eclipse integrated development environment to standalone command-line based interpreters, each with their own unique and often challenging installation and configuration requirements. To help enable other researchers to more easily utilize these frameworks and facilitate increased and robust reproducibility across end-user platforms, we present and make available containerized versions of a number of these PEPA frameworks. We have validated the functionality of these containers by testing them with models available f

关键词： Application virtualization Reproducibility of results Performance modeling Performance evaluation Robustness analysis parallel computing Process algebra Scalability

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Power Sharing and parallel Inverters Control in Islanded Microgrids

Power Sharing and Parallel Inverters Control in Islanded Mic...

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international symposium on Advanced Electrical and Communication Technologies (ISAECT)

作者： Ammeh Leila El Fadil Hassan Giri Fouad Tarek Ahmed-Ali Advanced Systems Engineering Laboratory Ibn Tofail University Kenitra Morocco Automatic Laboratory Caen University Normandie France

ISBN: (纸本)9781665437745

This paper deals with the control of parallel voltage source inverters (VSI) in microgrid islanded mode while sharing the active and reactive power required by the load. Firstly, an islanded microgrid composed of n distributed energy resources (DER) connected to each other through VSI and nonlinear load is modelled. Thereafter, a master slave based control strategy is proposed. One of the VSI is designated as a master and it is responsible for controlling the microgrid AC bus voltage and responsible, also, for setting the reference current to be supplied by the slave VSI. In the other hand, the slaves are responsible for controlling their output currents following the references received from the master VSI; in that way, the active and reactive power are shared among all the DER proportionally to their rated generated power. The control of the VSI voltage and current is ensured applying the backstepping technique. Using Lyapunov theory, the closed loop system is globally asymptotically stable. From the simulation case study, the proposed control strategy ensures the voltage control of the n parallel VSI as well as the power sharing between the n DER without being overloaded.

关键词： Reactive power Backstepping Fluctuations Voltage source inverters Simulation Microgrids Main-secondary

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