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检索条件"任意字段=International Symposium on Software Engineering for Parallel and Distributed Systems"

共 10743 条记录，以下是481-490 订阅

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Black-Box Stability Analysis Method for Dual parallel Pulse Power Load

Black-Box Stability Analysis Method for Dual Parallel Pulse ...

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

作者： Xu Chen Jianping Xu Ping Yang Zhengge Chen Jin Qi Xi Tang School of Electrical Engineering Southwest Jiaotong University Chengdu China

The impedance of power source of the microgrid cannot be regarded as infinite, thus it may cause stability problems, especially when the load is a pulse power load. The black box method can not be well applied to pulse power load. To address this issue, a black-box stability analysis method for system with parallel pulse loads is proposed in this paper. Based on the stability condition of the system with single load, the stability condition of the system with parallel load is derived. Finally, 3-D fitting Bode plot are given to analyze the stability of the system with parallel load. Simulations results are given to verify the analysis results.

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Crazy Nodes: Towards Ultimate Flexibility in Ubiquitous Big Data Stream engineering, Visualisation, and Analytics, in Smart Factories 11th

Crazy Nodes: Towards Ultimate Flexibility in Ubiquitous Big ...

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11th international symposium on Leveraging Applications of Formal Methods, Verification and Validation

作者： Soderi, Mirco Breslin, John G. Natl Univ Ireland Galway Ireland

ISBN: (纸本)9783031197611;9783031197628

Smart Factories characterize as context-rich, fast-changing environments where heterogeneous hardware appliances are found beside of also heterogeneous software components deployed in (or directly interfacing with) IoT devices, as well as in on-premise mainframes, and on the Cloud. This inherent heterogeneity poses major challenges particularly when a high degree of resiliency is needed, and the ubiquitously deployed software components must be replaced or reconfigured at real-time to respond to the most diverse events, ranging from an out-of-range sensor detection, to a new order issued by a customer. In this work, a software framework is presented, which allows to deploy, (re)configure, run, and monitor the most diverse software across all the three layers of the Smart Factory (edge, fog, Cloud), from remote, via API calls, in a standardised uniform manner, relying on containerization technologies, and on a variety of software technologies, frameworks, and programming languages, including Node-RED, MQTT, Scala, Apache Spark, and Kafka. The most recent advances in the framework design, implementation, and demonstration, which led to the introduction of the so-called Crazy Nodes, are presented and motivated. A comprehensive proof-of-concept is given, where user interfaces and distributed systems are created from scratch via API calls to implement AI-based alerting systems, Big Data stream filtering and transformation, AI model training, storage, and usage for one-shot as well as stream predictions, and real-time Big Data visualization through line plots, histograms, and pie charts.

关键词： Smart manufacturing Resilient manufacturing Cloud manufacturing Artificial intelligence AI distributed system System of systems Ubiquitous computing Stream processing Stream visualization Micro-service Application programming interface API

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VTrain: A Simulation Framework for Evaluating Cost-Effective and Compute-Optimal Large Language Model Training 57

VTrain: A Simulation Framework for Evaluating Cost-Effective...

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57th Annual IEEE/ACM international symposium on Microarchitecture, MICRO 2024

作者： Bang, Jehyeon Choi, Yujeong Kim, Myeongwoo Kim, Yongdeok Rhu, Minsoo KAIST School of Electrical Engineering Korea Republic of Samsung Advanced Institute of Technology Korea Republic of

ISBN: (纸本)9798350350579

As large language models (LLMs) become widespread in various application domains, a critical challenge the AI community is facing is how to train these large AI models in a cost-effective manner. Existing LLM training plans typically employ a heuristic based parallel training strategy which is based on empirical observations rather than grounded upon a thorough examination of the search space of LLM parallelization. Such limitation renders existing systems to leave significant performance left on the table, wasting millions of dollars worth of training cost. This paper presents our profiling-driven simulator called vTrain, providing AI practitioners a fast yet accurate software framework to determine an efficient and cost-effective LLM training system configuration. We demonstrate vTrain's practicality through several case studies, e.g., effectively evaluating optimal training parallelization strategies that balances training time and its associated training cost, efficient multi-Tenant GPU cluster schedulers targeting multiple LLM training jobs, and determining a compute-optimal LLM model architecture given a fixed compute budget. © 2024 IEEE.

关键词： Costs

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Extending Composable Data Services into SmartNICs

Extending Composable Data Services into SmartNICs

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

作者： Craig Ulmer Jianshen Liu Carlos Maltzahn Matthew L. Curry Scalable Modeling & Analysis Sandia National Laboratories Livermore CA USA Comp. Science & Engineering UC Santa Cruz Santa Cruz CA USA Scalable System Software Sandia National Laboratories Albuquerque NM USA

Advanced scientific-computing workflows rely on composable data services to migrate data between simulation and analysis jobs that run in parallel on high-performance computing (HPC) platforms. Unfortunately, these services consume compute-node memory and processing resources that could otherwise be used to complete the workflow’s tasks. The emergence of programmable network interface cards, or SmartNICs, presents an opportunity to host data services in an isolated space within a compute node that does not impact host resources. In this paper we explore extending data services into SmartNICs and describe a software stack for services that uses Faodel and Apache Arrow. To illustrate how this stack operates, we present a case study that implements a distributed, particle-sifting service for reorganizing simulation results. Performance experiments from a 100-node cluster equipped with 100Gb/s BlueField-2 SmartNICs indicate that current SmartNICs can perform useful data management tasks, albeit at a lower throughput than hosts.

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8th international symposium on Dependable software engineering: Theories, Tools and Applications, SETTA 2022

8th International Symposium on Dependable Software Engineeri...

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8th international symposium on Dependable software engineering: Theories, Tools and Applications, SETTA 2022

ISBN: (纸本)9783031212123

The proceedings contain 14 papers. The special focus in this conference is on Dependable software engineering: Theories, Tools and Applications. The topics include: Integration of Multiple Formal Matrix Models in Coq;on-The-Fly Bisimilarity Checking for Fresh-Register Automata;LOGIC: A Coq Library for Logics;Diversifying a parallel SAT Solver with Bayesian Moment Matching;MTUL: Towards Mutation Testing of Unsupervised Learning systems;COOL-MC: A Comprehensive Tool for Reinforcement Learning and Model Checking;VM Migration and Live-Update for Reliable Embedded Hypervisor;mastery: Shifted-Code-Aware Structured Merging;KCL: A Declarative Language for Large-Scale Configuration and Policy Management;eqFix: Fixing LaTeX Equation Errors by Examples;Translating CPS with Shared-Variable Concurrency in SpaceEx;a Contract-Based Semantics and Refinement for Simulink.

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A Genetic Algorithm based parallel Task Planning Method for Cooperative MRS

A Genetic Algorithm based Parallel Task Planning Method for ...

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software engineering, Artificial Intelligence, Networking and parallel/distributed Computing (SNPD-Winter), ACIS international Winter Conference on

作者： Li Yu Wang Tianyang Zhang Zhongqiu Ren Xiaokun Northwestern Polytechnical University Xi'an China School of Computer Northwestern Polytechnical University Xi'an China Center of Information Northwestern Polytechnical University Xi'an China

With in the trend of intelligence, task cooperation has been emerging as one main feature for Multiple Robot systems (MRS) and applications, typically Multi-UAV (MUAV) system. For such swarm cooperative systems, how to plan and map their tasks to proper members within systems optimally and fast has been one vital issue that affects the efficiency of cooperation. So, in this article, a two-level task model is firstly established, which is the foundation of automatic task parsing and planning. Further, a Genetic Algorithm (GA) based parallel Task Planning algorithm PTP-GA is proposed and designed, the goal of which is to improve the performance via cluster related tasks together and separating the dividing the solution space. Particularly, several constrained operators are designed to warrantee both the randomness and elitist individuals or segments. Finally, this proposed method is verified within a simulated scenario, and it shows that the performance of this parallel algorithm is indeed improved.

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Security Issues and Challenges of Big Data Analytics 7

Security Issues and Challenges of Big Data Analytics

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7th international Conference on parallel, distributed and Grid Computing, PDGC 2022

作者： Verma, Richa Bhatt, Ravindara Jaypee University of Information Technology Computer Science and Engineering Waknaghat P.O. Teh Kandaghat Distt. H.P. Solan173 234 India

ISBN: (纸本)9781665454018

Big data analytics (BDA) is a key technology that is used in a variety of corporate fields, including the welfare medical profession. In the actual world, there is no such thing as a flawless security solution for a certain activity or *** growth has provided a variety of different ways over the years that may aid in the development of unique algorithms and techniques. The potential for cyberthreats and cyberattacks grows as more consumer and organizational information is digitized and collected for data analytics. Security and tactical information are two important areas where big data analytics is anticipated to make a substantial contribution. Current security problem and tracking systems (or SIEM) systems, which typically operate with a small selection of traditional data sources like firewalls, intrusion detection systems, etc., in a software system, do not adequately address security analytics in a big data context. The paper addressed the security challenges of big data analytics in social network platform. The paper also looked at the user engagement in different social media platforms. © 2022 IEEE.

关键词： Big data

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FPGA-based Implementation for Industrial Motion Control System

FPGA-based Implementation for Industrial Motion Control Syst...

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

作者： Claudio Rubattu Antonio Ledda Francesco Ratto Chaitanya Jugade Dip Goswami Francesca Palumbo University of Sassari Sassari Italy Eindhoven University of Technology Eindhoven AZ Netherlands University of Cagliari Cagliari Italy

ISBN: (数字)9798350364606

ISBN: (纸本)9798350364613

In these years of severe chip shortage, it is even more important to improve the efficiency of chip manufacturing. As is well known, manufacturing phases rely on increasingly intelligent production machinery, which must ensure high quality and large volumes. That is true also for die-bonding machines, which are required to satisfy very high standards of speed and accuracy. For this purpose, such devices have started to evaluate the possibility of adopting computer vision algorithms for automatic recognition of wafer positioning and die size. This paper proposes an FPGA accelerated implementation of one of these algorithms, demonstrating the advantages of using this technology to this end and paving the way towards a larger adoption of this kind of acceleration platform for the different tasks composing modern industrial motion control systems. At the state of the art, such systems are typically managed with software-oriented solutions, which may not be sufficient in the case of highly restrictive requirements in terms of execution time. For this reason, the design flow considered the use of high-level hardware design, which offers a more software-friendly solution to developers without in-depth hardware knowledge. The proposed solution is a state-of-the-art implementation for execution time and resources of programmable logic while enabling higher precision in terms of die position estimation.

关键词： Temperature distribution System performance Process control Production software Manufacturing Timing

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A Blockchain-Assisted Federated Learning Method for Recommendation systems

A Blockchain-Assisted Federated Learning Method for Recommen...

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international symposium on parallel and distributed Processing with Applications, ISPA

作者： Hang Zhang Hao Tian Cheng Chen Chen Tian Wanchun Dou State Key Laboratory for Novel Software Technology Nanjing University Nanjing China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

Due to the privacy advantages of federated learning (FL), federated recommendation systems (FedRSs) are gaining popularity for improving recommendation performance through training on local data. However, FedRSs frequently face the significant challenge of high communication costs between the server and clients. Most FedRSs utilize a client-server communication architecture, leading to heavy communication loads and single points of failure due to dependence on a central server. Clients may also encounter problems due to limited communication resources. In view of this challenge, in this paper, we propose a blockchain-assisted federated learning method at edge for communication-efficient recommendation systems, named BFedRec. Specifically, BFedRec reduces reliance on the central server by utilizing blockchain systems on edge servers to aggregate and distribute the recommendation model. To mitigate the high communication costs between clients and blockchain in each iteration, a communication-efficient training algorithm is used that trains the recommendation model directly on low-rank compressed parameters. Finally, we conduct extensive experiments on real-world datasets to verify the communication efficiency of BFedRec compared to existing methods. The experimental results show that BFedRec effectively improves communication efficiency without compromising recommendation performance.

关键词： Training Learning systems distributed processing Data privacy Costs Federated learning Blockchains Servers Recommender systems Faces

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A Solution for Conference Room Cluster Audio System Based on distributed Architecture

A Solution for Conference Room Cluster Audio System Based on...

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ACIS international Conference on software engineering, Artificial Intelligence, Networking, and parallel/distributed Computing (SNPD)

作者： Xiaoyi Xu Xin Zhang Zenglai Wei School of Music and Recording Arts Communication University of China Beijing China School of Computer and Cyber Sciences Communication University of China Beijing China

ISBN: (数字)9798350391954

ISBN: (纸本)9798350391961

With the rapid development of information technology, people have put forward higher requirements for the audio-visual experience and usage functions of conference spaces. The traditional, single-function conference room configuration can no longer adapt to the diverse needs of modern work and interactive activities. How to achieve efficient management and control, seamless interconnection, and resource sharing of audio systems across spaces, while ensuring the acoustic characteristics and flexibility of each independent space, has become a core issue that needs to be urgently resolved in building a multi-hall, multifunctional conference room cluster. Based on the audio system project of the Academic Center of the Communication University of China, this paper proposes a solution for a conference room cluster audio system based on a distributed architecture. This solution not only overcomes the limitations of traditional systems in terms of scalability, collaborative work, and resource scheduling but also promotes lossless transmission, real-time processing, and adaptive configuration of audio signals. Thus, it ensures the consistency and high quality of the audio experience within the entire cluster, providing practical guidance for the design and optimization of future conference room audio systems.

关键词： Technological innovation Federated learning Audio systems Scalability Computer architecture Aerospace electronics Propagation losses

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