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Preface to the special issue on Formal Approaches to parallel and distributed systems 2018

JOURNAL OF LOGICAL AND ALGEBRAIC MEthODS IN PROGRAMMING 2020年 116卷

作者： Loulergue, Frederic No Arizona Univ Sch Informat Comp & Cyber Syst Flagstaff AZ 86011 USA Univ Orleans INSA Ctr Val Loire LIFO EA 4022 Orleans France

this special issue contains extended versions of selected papers from the 5th international Symposium on Formal Approaches to parallel and distributed systems (4PAD 2018). the symposium was held in Orleans, France on July 19th, 2020 in conjunction with the 2018 international conference on High Performance computing & Simulation (HPCS 2018). (C) 2020 Elsevier Inc. All rights reserved.

关键词： distributed systems Synchronous and asynchronous communication Choregraphies CPU-GPU heterogeneous systems parallelism semantics Synthesis

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Comparing thread Migration, Mobile Agents, and ABM Simulators in distributed Data Analysis 19th

Comparing Thread Migration, Mobile Agents, and ABM Simulator...

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19th international conference on Advances in Practical Applications of Agents, Multi-Agent systems, and Social Good (PAAMS)

作者： Wenger, Maxwell Acoltzi, Jonathan Fukuda, Munehiro Univ Washington Comp & Software Syst Bothell WA 98011 USA

ISBN: (纸本)9783030857394;9783030857387

Many scientific datasets are generated in a given data structure (e.g., a graph) and are reused for various analyses. From this viewpoint, instead of streaming these datasets into conventional big-data tools such as MapReduce or Spark, we should maintain their data structures over distributed memory and repeat deploying mobile computing units to the datasets. Since thread migration, mobile agents, and parallel ABM (agent-based modeling) simulators enable migration of execution entities, this paper looks at four Java-based representative systems: JCilk, IBM Aglets, Repast Simphony, and the MASS library. Our analysis of their programmability and parallel performance demonstrates that MASS can competitively perform distributed data analysis in an emergent collective group behavior among reactive agents.

关键词： thread migration Mobile agents Agent-based modeling distributed memory

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Issues and Algorithm of distributed Shared Memory 4

Issues and Algorithm of Distributed Shared Memory

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4th international conference on Innovative computing (ICIC)

作者： Ahmad, Mian Basam Sagheer, Sundas Univ Management & Technol Dept Comp Sci Lahore Pakistan Univ Management & Technol Dept Software Engn Lahore Pakistan

ISBN: (纸本)9781665400916

Internet of things is a rapidly growing industry, and there are more connected devices than humans. there are unlimited internet of things devices around us. the scope of these devices has increased manifold in recent years in different areas like healthcare, unmanned vehicles, automatic monitoring systems, and smart homes, etc. these connected devices produce lots of data that need to be processed to achieve the goal of automation in daily life. the cloud provides many centralized solutions to process data using powerful resources in real-time, but there could be latency issues due to increased network traffic. So a distributed solution is much needed to meet this growing demand of processing data in parallel. In this paper, we propose a distributed shared memory [18] abstraction for the internet of things that uses a graph-aware partitioning algorithm and uses smart message passing techniques to process data in distributed and parallel fashion [19].

关键词： Internet of things

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ICNSC 2022 - Proceedings of 2022 IEEE international conference on Networking, Sensing and Control: Autonomous Intelligent systems

ICNSC 2022 - Proceedings of 2022 IEEE International Conferen...

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19th IEEE international conference on Networking, Sensing and Control, ICNSC 2022

ISBN: (纸本)9781665472432

the proceedings contain 144 papers. the topics discussed include: hybrid neighborhood search algorithm for multi-product hybrid disassembly line balancing problem considering multi-skill workers;generic multi-agent cooperative control via finite-time distributed MPC;multi-scale feature fusion filtering module in convolutional neural networks;a review of observability issues in hospital information system;constraint programming for a novel integrated optimization of blocking job shop scheduling and variable-speed transfer robot assignment;anti-sideslip line of sight method-based path tracking control for a multi-joint snake robot;an efficient metaheuristic algorithm for solving soft-clustered vehicle routing problems;detection transformer: ultrasonic echo signal inclusion detection with transformer;design of resilient supervisory control for autonomous connected vehicles approaching unsignalized intersection in presence of communication delays;a parallel neighborhood search algorithm for hybrid disassembly line balancing problem considering disabled workers;and graph regularized nonnegative latent factor analysis model for temporal link prediction in cryptocurrency transaction networks.

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Experiments Using a Software-distributed Shared Memory, MPI and 0MQ over Heterogeneous computing Resources

Experiments Using a Software-Distributed Shared Memory, MPI ...

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26th international conference on parallel and distributed computing (Euro-Par)

作者： Cudennec, Loic Trabelsi, Kods CEA LIST PC 172 F-91191 Gif Sur Yvette France DGA MI Dept Artificial Intelligence BP 7 F-35998 Rennes Armees France

ISBN: (纸本)9783030715939;9783030715922

distributed heterogeneous computing systems escalate the problem of choosing the appropriate programming model. Programming models such as message passing are efficient but require low-level management of communications. Higher level of programming such as shared memory are convenient for the application design but they usually have performance issues. With the recent development of distributed heterogeneous systems and new protocols to access remote memories, there is an opportunity for distributed shared memory systems to offer a satisfying level of abstraction while not giving up on performance. In this paper a video processing application is written using MPI, 0MQ and an in-house software-distributed shared memory (S-DSM) backend and deployed over a set of heterogeneous computing boards. Results show that 0MQ implementation is the most efficient but at the price of writing the application with the targeted platform in mind. the S-DSM implementation runs up to 2 times faster than the pure OpenMPI implementation and competes with 0MQ when the data granularity is small.

关键词： Heterogeneous computing distributed computing distributed shared memory Message passing

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Towards On-the-fly Self-Adaptation of Stream parallel Patterns 29

Towards On-the-fly Self-Adaptation of Stream Parallel Patter...

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29th Euromicro international conference on parallel, distributed and Network-Based Processing (PDP)

作者： Vogel, Adriano Mencagli, Gabriele Griebler, Dalvan Danelutto, Marco Fernandes, Luiz Gustavo Pontifical Catholic Univ Rio Grande do Sul PUCRS Sch Technol Porto Alegre RS Brazil Tres de Maio Fac SETREM Lab Adv Res Cloud Comp LARCC Tres De Maio Brazil Univ Pisa UNIPI Comp Sci Dept Pisa Italy

ISBN: (纸本)9781665414555

Stream processing applications compute streams of data and provide insightful results in a timely manner, where parallel computing is necessary for accelerating the application executions. Considering that these applications are becoming increasingly dynamic and lung-running, a potential solution is to apply dynamic runtime changes. However, it is challenging for humans to continuously monitor and manually self-optimize the executions. In this paper, we propose self-adaptiveness of the parallel patterns used, enabling flexible on-the-fly adaptations. the proposed solution is evaluated with an existing programming framework and running experiments with a synthetic and a real-world application. the results show that the proposed solution is able to dynamically self-adapt to the most suitable parallel pattern configuration and achieve performance competitive with the best static cases. the feasibility of the proposed solution encourages future optimizations and other applicabilities.

关键词： parallel computing parallel Patterns parallelism Abstractions Self adaptive systems Stream Processing

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Combining thread throttling and Mapping to Optimize the EDP of parallel Applications 29

Combining Thread Throttling and Mapping to Optimize the EDP ...

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29th Euromicro international conference on parallel, distributed and Network-Based Processing (PDP)

作者： Berned, Gustavo P. Medeiros, thiarles S. Serpa, Matheus Rossi, Fabio D. Luizelli, Marcelo C. Navaux, Philippe O. Beck, Antonio Carlos S. Lorenzon, Arthur F. Fed Inst Educ Sci & Technol Farroupilha Santa Maria RS Brazil Univ Fed Rio Grande do Sul Inst Infonnat Porto Alegre RS Brazil Fed Univ Pampa Campus Alegrete Bage RS Brazil

ISBN: (纸本)9781665414555

thread-throttling and mapping strategies have been used together to make better use of hardware resources and improve the energy-delay product (EDP) of high-performance computing (HPC) systems. However, the design space exploration significantly grows with the increasing number of cores in those systems, making the task of finding the ideal number of active threads and allocating strategy a challenging task. On top of that, parallel applications present various patterns, such as irregularity, unbalanced computations, or high rates of communications. Given these considerations, we propose ETTM, an EDP-aware thread-throttling and mapping optimization strategy that automatically finds an ideal combination of number of threads and thread mapping strategy. With the execution of eighteen well-known benchmarks on three multicore architectures, we show that EDP can be significantly improved when running applications with the solution found by EETM1 .

关键词： thread-level parallelism thread mapping Energy-delay product

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An Intelligent parallel distributed Streaming Framework for near Real-time Science Sensors and High-Resolution Medical Images 21

An Intelligent Parallel Distributed Streaming Framework for ...

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50th international conference on parallel Processing (ICPP)

作者： Shivadekar, Samit Mangalagiri, Jayalakshmi Phuong Nguyen Chapman, David Halem, Milton Gite, Rahul Univ Maryland Baltimore Cty Baltimore MD 21228 USA OpenKneck Inc Halethorpe MD USA

ISBN: (纸本)9781450384414

Our goals are to address challenges such as latency, scalability, throughput and heterogeneous data sources of streaming analytics and deep learning pipelines in science sensors and medical imaging applications. We present a prototype Intelligent parallel distributed Streaming Framework (IPDSF) that is capable of distributed streaming processing as well as performing distributed deep training in batch mode. IPDSF is designed to run streaming Artificial Intelligent (AI) analytic tasks using data parallelism including partitions of multiple streams of short time sensing data and high-resolution 3D medical images, and fine grain tasks distribution. We will show the implementation of IPDSF for two real world applications, (i) an Air Quality Index based on near real time streaming of aerosol Lidar backscatter and (ii) data generation of Covid-19 computing Tomography (CT) scans using deep learning. We evaluate the latency, throughput, scalability, and quantitative evaluation of training and prediction compared against a baseline single instance. As the results, IPDSF scales to process thousands of streaming science sensors in parallel for Air Quality Index application. IPDSF uses novel 3D conditional Generative Adversarial Network (cGAN) training using parallel distributed Graphic Processing Units (GPU) nodes to generate realistic 3D high resolution Computed Tomography scans of Covid-19 patient lungs. We will show that IPDSF can reduce cGAN training time linearly with the number of GPUs.

关键词： distributed streaming Data parallelism Deep Learning Lidar backscatter Computed Tomography cGAN

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Using Stream Processing for Real-Time Clock Drift Correction in distributed Data Processing systems

Using Stream Processing for Real-Time Clock Drift Correction...

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international Computer Sciences and Information Technologies (CSIT)

作者： Roman Moravskyi Yevheniya Levus Software Department Lviv Polytechnic National University Lviv Ukraine

ISBN: (数字)9798331542634

ISBN: (纸本)9798331542641

In large-scale smart device networks, such as those used in metering systems, the internal clocks of one-way communication devices can drift over time, leading to inaccuracies that impact data-driven decision-making and operational efficiency. Existing solutions often rely on postcollection corrections or synchronization methods that are not feasible for systems requiring real-time accuracy. this study evaluates a method for correcting time drift in smart devices using stream processing. By leveraging a distributed architecture with Apache Kafka, Flink, and OpenSearch, the proposed system processes a continuous stream of device time points at a high rate, ensuring accurate and scalable time correction. Benchmark tests demonstrate the system's capability to maintain low backpressure and high throughput under varying conditions. the findings suggest that the proposed approach is effective for real-time clock drift correction in large-scale networks, offering insights for future integration into Meter Data Management systems (MDMS).

关键词： Performance evaluation Meters Computer network reliability parallel processing Benchmark testing Data processing Real-time systems Synchronization Smart devices Clocks

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Load Balancing Optimization for Transformer in distributed Environment 27

Load Balancing Optimization for Transformer in Distributed E...

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27th IEEE international conference on parallel and distributed systems, ICPADS 2021

作者： Ma, Delu Lei, Zhou Chen, Shengbo Wang, Peng School of Computer Engineering and Science Shanghai University Shanghai200444 China Shanghai Key Laboratory of Computer Software Testing and Evaluating Shanghai201112 China

ISBN: (纸本)9781665408783

In recent years, the demand for artificial intelligence applications has increased dramatically. Complex models can promote machine learning to achieve excellent results, but computing efficiency has gradually reached a bottleneck. therefore, more researchers are exploring the improvement of the efficiency of intelligent computing systems. distributed machine learning can improve the efficiency of model training and inference, but problems such as communication delay and load imbalance between computing nodes still exist. In the multi-GPU distributed computing environment, this paper takes the vision field algorithm VIT (vision transformer) as the optimization object, which has the advantage of convenient parallel training, and proposes several related solutions. Firstly, the parameter server is used as the system logic architecture and in order to reduce the idleness of the computing devices during the training process, the device working status query mechanism is designed to realize load balancing. Secondly, combined with the pre-trained small VIT algorithm model, semi-asynchronous communication method is proposed to reduce the communication overhead of computing devices and accelerate global convergence. the results of this experiment carried out in the existing distributed environment has demonstrated that compared with the existing synchronization method, the computational efficiency has been improved well under the premise of slightly reducing the accuracy. © 2021 IEEE.

关键词： Computation theory

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