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International workshop/Symposium on distributed Simulation and real-time Applications (DS-RT)

作者： Robson E. De Grande Alberto Falcone Alfredo Garro Depart. of Computer Science Brock University St. Catharines Canada Depart. of Informatics Modeling Electronics and Systems Engineering University of Calabria Italy

ISBN: (数字)9798331527211

ISBN: (纸本)9798331527228

SpaceFOM is the reference standard adopted by space agencies for simulating space missions. Although specifically designed for handling space systems, it currently faces a significant limitation when simulating interplanetary missions: a fixed Federation time Step. This constraint hinders accurate and flexible modeling of space missions, which limits the dynamic changes of simulation pace, especially during critical phases that require particular temporal granularities. This work proposes extending the SpaceFOM standard to address this issue by enabling dynamic adjustment of Federation time Step granularity. The proposed solution allows fine-grained time steps for mission-critical phases and coarse-grained steps for extended phases while smoothly combining continuous temporal progression. Furthermore, the proposed solution is general-purpose and can be applied to other domains requiring dynamic temporal granularity.

关键词： Mars Accuracy Interplanetary exploration Space missions Mission critical systems Refining real-time systems Timing Standards Intelligent transportation systems

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parallel Data Stream Anonymization Methods: A Review 2

Parallel Data Stream Anonymization Methods: A Review

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2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022

作者： Trivedi, Brinit Degadwala, Sheshang Vyas, Dhairya Sigma Institute of Engineering Dept. of Comp. Eng Gujarat Vadodara India Shree Drashti Infotech Llp Gujarat Vadodara India

ISBN: (纸本)9781665400527

Sustainable stream processing algorithms have gained popularity in recent years. Flow control is a way of searching and modifying real-time data streams. Missing values are ubiquitous in real-world data streams, making data stream privacy challenging to safeguard. On the other hand, most privacy preservation methods need not take absent values into account when developed. They can anonymize data in certain study, however this results in data loss. This research proposes a unique parallel distributed approach for protecting privacy while using incomplete data streams. This method uses a production computational system to continually anonymize data streams, using clustering to construct each tuple. It clusters data in partial and complete forms using variable and array dimensions as similarity metrics. In order to prevent values and outliers' pollution, a generalization approach that is based on more than matches is used. The experiments used real data to compare current systems with varied settings. This research will cover several anonymization mechanisms and their advantages. There are also drawbacks. Finally, the future of continuous data anonymization research has been explored. © 2022 IEEE.

关键词： Measurement Data privacy Privacy Pollution distributed databases Production real-time systems

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铁路货车钩舌检修数字孪生车间的研究与应用

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计算机集成制造系统 2024年第7期30卷 2474-2485页

作者：杨康吴少培董志宇李国芳丁旺才兰州交通大学机电工程学院甘肃兰州730070

为了实现对铁路货车检修车间的实时透明管控,提高车间管理的信息化和智能化水平。首先,基于数字孪生技术,提出一种数字孪生检修车间六维模型,介绍了系统核心功能和开发流程,并详细阐述了数据采集及交换、三维可视化场景构建,被检对象生... 详细信息

为了实现对铁路货车检修车间的实时透明管控,提高车间管理的信息化和智能化水平。首先,基于数字孪生技术,提出一种数字孪生检修车间六维模型,介绍了系统核心功能和开发流程,并详细阐述了数据采集及交换、三维可视化场景构建,被检对象生成等全要素精准建模过程。其次,基于分布式MQTT构架的数据采集及交换的方法,建立多源异构数据流转节点的状态矩阵,利用嵌入式设备、采集卡、传感器,逻辑控制器与车间管控系统进行数据交换,结合检修车间设备、物料、产线等检修全过程动态模型,构建了虚实交互映射的检修车间数字孪生系统。最后,通过基于数据挖掘的钩舌检修跟踪、检修工艺甘特图等技术输出,展示了数字孪生关键技术在钩舌智能检修中的应用场景,验证了所提方法的有效性,同时为数字孪生在智能轨道交通中的应用提供参考。

关键词：数字孪生检修车间实时信息铁路货车

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Towards Efficient Large-Scale Interprocedural Program Static Analysis on distributed Data-parallel Computation

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IEEE TRANSACTIONS ON parallel AND distributed systems 2021年第4期32卷 867-883页

作者： Gu, Rong Zuo, Zhiqiang Jiang, Xi Yin, Han Wang, Zhaokang Wang, Linzhang Li, Xuandong Huang, Yihua Nanjing Univ State Key Lab Novel Software Technol Nanjing 210023 Peoples R China Nanjing Univ Dept Comp Sci & Technol Nanjing 210023 Peoples R China

Static program analysis has been widely applied along the whole process of the program development for bug detection, code optimization, testing, etc. Although researchers have made significant work in static program analysis, it is still challenging to perform sophisticated interprocedural analysis on large-scale modern software. The underlying reason is that interprocedural analysis for large-scale modern software is highly computation- and memory-intensive, leading to poor efficiency and scalability. In this article, we introduce an efficient distributed and scalable solution for sophisticated static analysis. Specifically, we propose a data-parallel algorithm and a join-process-filter computation model for the CFL-reachability-based interprocedural analysis. Based on that, an efficient distributed static analysis engine called BigSpa is developed, which is composed of an offline batch static program analysis system and an online incremental static program analysis system. The BigSpa system has high generality and can support all kinds of static analysis tasks that can be expressed as CFL reachability problems. The performance of BigSpa is evaluated on real-world large-scale software datasets. Our experiments show that the offline batch system can exceed an order of magnitude compared with the most advanced analysis tools available on performance, and for incremental analysis with small batch updates on the same data sets, the online analysis system can achieve near real-time response, which is very fast and flexible.

关键词： Static analysis Software Scalability Task analysis Optimization Big Data Computational modeling Interprocedural static analysis distributed systems data-parallel computation

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High Quality of Service in Future Electrical Energy systems: A New time-Domain Approach

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IEEE TRANSACTIONS ON SUSTAINABLE ENERGY 2021年第2期12卷 1196-1205页

作者： Miao, Xia Ilic, Marija D. MIT Lab Informat & Decis Syst 77 Massachusetts Ave Cambridge MA 02139 USA

In this paper we study dynamical distortion problems in future electrical energy systems with high renewable penetration. We introduce a new time-domain modeling of electrical energy systems comprising inverter-controlled distributed energy resources (DERs). This modeling is first used to quantify the relations between distortions and real/reactive power dynamics. Next, to ensure acceptable Quality of Service (QoS), a novel nonlinear distributed inverter control is introduced. Sufficient conditions are established for the guaranteed performance of the proposed control. These conditions further support the practical implementation of the derived controller. The effectiveness of this enhanced control is illustrated using simulations for the case of avoiding system instability during sudden grid reconfigurations. Simulations also show that distortions can be suppressed in systems with parallel-connected solar photovoltaics (PVs).

关键词： Nonlinear distortion time-domain analysis Quality of service Voltage control Reactive power Load modeling Inverters distributed control inverter control solar photo-voltaics (PVs) time-domain modeling of microgrids stability

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EDGES: An Efficient distributed Graph Embedding System on GPU Clusters

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IEEE TRANSACTIONS ON parallel AND distributed systems 2021年第7期32卷 1892-1902页

作者： Yang, Dongxu Liu, Junhong Lai, Junjie NVIDIA Beijing 100102 Peoples R China

Graph embedding training models access parameters sparsely in a "one-hot" manner. Currently, the distributed graph embedding neural network is learned by data parallel with the parameter server, which suffers significant performance and scalability problems. In this article, we analyze the problems and characteristics of training this kind of models on distributed GPU clusters for the first time, and find that fixed model parameters scattered among different machine nodes are a major limiting factor for efficiency. Based on our observation, we develop an efficient distributed graph embedding system called EDGES, which can utilize GPU clusters to train large graph models with billions of nodes and trillions of edges using data and model parallelism. Within the system, we propose a novel dynamic partition architecture for training these models, achieving at least one half of communication reduction compared to existing training systems. According to our evaluations on real-world networks, our system delivers a competitive accuracy for the trained embeddings, and significantly accelerates the training process of the graph node embedding neural network, achieving a speedup of 7.23x and 18.6x over the existing fastest training system on single node and multi-node, respectively. As for the scalability, our experiments show that EDGES obtains a nearly linear speedup.

关键词： Training Data models Servers Graphics processing units Computational modeling Neural networks Training data Large-scale distributed training graph node embedding GPU clusters parallel algorithm scalability

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TaiChi: A Hybrid Compression Format for Binary Sparse Matrix-Vector Multiplication on GPU

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IEEE TRANSACTIONS ON parallel AND distributed systems 2022年第12期33卷 3732-3745页

作者： Gao, Jianhua Ji, Weixing Tan, Zhaonian Wang, Yizhuo Shi, Feng Beijing Inst Technol Sch Comp Sci & Technol Beijing 100081 Peoples R China

Binary Sparse Matrix-Vector Multiplication (SpMV) is a heavy computational kernel in weblink analysis, integer factorization, compressed sensing, spectral graph theory, and other domains. Testing several popular GPU-based SpMV implementations on 400 sparse matrices, we observed that data transfer to GPU memory accounts for a large part of the total computation time. The transfer of constant value "1"s can be easily eliminated for binary sparse matrices. However, compressing index arrays has always been a great challenge. This article proposes a new compression format TaiChi to further reduce index data copies and improve the performance of SpMV, especially for diagonally dominant binary sparse matrices. Input matrices are first partitioned into relatively dense and ultra-sparse areas. Then the dense areas are encoded inversely by marking "0"s, while the ultra-sparse area is encoded by marking "1"s. We also designed a new SpMV algorithm only using addition and subtraction for binary matrices based on our partition and encoding format. Evaluation results on real-world binary sparse matrices show that our hybrid encoding for binary matrix significantly reduces the data transfer and speeds up the kernel execution. It achieves the highest transfer and kernel execution speedups of 5.63x and 3.84x on GTX 1080 Ti, 3.39x and 3.91x on Tesla V100.

关键词： Sparse matrices Kernel Graphics processing units Indexes Arrays Encoding Partitioning algorithms Binary sparse matrix SpMV GPU parallel computing mathematical morphology

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基于FPGA的新能源低压直流配电系统暂态实时仿真研究

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电工技术学报 2024年第17期39卷 5365-5378,5393页

作者：王守相张春雨赵倩宇天津大学教育部智能电网重点实验室天津300072 天津市电力系统仿真控制重点实验室天津300072

对新能源低压直流配电系统开展暂态实时仿真研究对优化其运行控制具有重要作用。由于现场可编程门阵列(FPGA)内部集成了大量具有不同功能的电路,FPGA正成为电力系统暂态实时仿真领域主要的计算载体之一。该文面向新能源低压直流配电系... 详细信息

对新能源低压直流配电系统开展暂态实时仿真研究对优化其运行控制具有重要作用。由于现场可编程门阵列(FPGA)内部集成了大量具有不同功能的电路,FPGA正成为电力系统暂态实时仿真领域主要的计算载体之一。该文面向新能源低压直流配电系统的暂态实时仿真需求,开发了一种基于FPGA的包含小型分布式风力发电、光伏发电以及蓄电池储能单元的新能源低压直流配电系统暂态实时仿真器。首先,研究构建了分布式发电单元和典型控制回路的计算模块,利用FPGA的并行计算特性并结合“算法-结构-有效匹配(AAA)”理念建立了底层模块串并联混合求解结构;然后,在节点分析法的框架下,建立了一种结合矩阵LDU分解和有向无环图(DAG)的电气系统节点电导矩阵并行求解方法;最后,在建立电气系统与控制系统并行求解架构的基础上,开发了一种基于FPGA的新能源低压直流配电系统暂态实时仿真器,通过将其仿真结果与PSCAD/EMTDC离线仿真平台的计算结果进行对比,验证了所开发暂态实时仿真器的有效性和准确性。

关键词：现场可编程门阵列(FPGA) 实时仿真分布式发电低压直流配电系统并行计算

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distributed, Continuous and real-time Trajectory Similarity Search

Distributed, Continuous and Real-time Trajectory Similarity ...

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International Symposium on parallel and distributed Computing

作者： Salman Ahmed Shaikh Hiroyuki Kitagawa Akiyoshi Matono Artificial Intelligence Research Center National Institute of Advanced Industrial Science and Technology Tokyo Japan International Institute for Integrative Sleep Medicine University of Tsukuba Tsukuba Japan

ISBN: (数字)9798350369199

ISBN: (纸本)9798350369205

Moving objects’ trajectory data is becoming increasingly available with the omnipresent GPS-equipped devices, e.g., smart phones, smart watches, etc. Identification of similar trajectories is a fundamental requirement of many real-world applications, for instance, car pooling, road planning, epidemic contact tracing. There exist a number of studies focusing on trajectory similarity search, where given a query trajectory, similar trajectories are searched from a trajectory store. GPS devices generate trajectories as a continuous data stream, highlighting the critical need for real-time and continuous trajectory similarity search. Thus, given a trajectories stream ($S_{\Gamma}$) and a trajectory store (R), we propose a distributed, continuous and real-time similarity search between $S_{\Gamma}$ and R. The proposed method employs an index-based strategy to facilitate effective similarity search, with the added capability of execution in distributed environments to ensure scalable processing. A comprehensive empirical study is provided to demonstrate the efficiency and pruning capability of the proposed approach.

关键词： Epidemics Roads Focusing real-time systems Trajectory Planning Object recognition distributed computing Smart phones Global Positioning System

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Practical Tie-Breaking for parallel/distributed Simulations

Practical Tie-Breaking for Parallel/Distributed Simulations

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International workshop/Symposium on distributed Simulation and real-time Applications (DS-RT)

作者： Andrea Piccione Alessandro Pellegrini Huawei Munich Research Center Tor Vergata University of Rome

In this paper, we discuss a tie-breaking strategy based on a bitwise comparison of event payload that allows parallel and distributed discrete-event simulations to observe a deterministic order in the execution of events, even in the presence of event ties. This approach provides practical usability whenever model-assisted tie-breaking is unavailable, thus ensuring that multiple simulation executions provide deterministic behaviour and repeatable results. Moreover, it ensures that the selected order of events is also consistent with sequential executions. We discuss the theory behind this strategy and experimentally show that the performance drop is imputable to event queue management when relying on tie-breaking strategies like the ones discussed in this work.

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