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检索条件"任意字段=9th International Conference on Algorithms and Architectures for Parallel Processing"

共 2826 条记录，以下是321-330 订阅

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Technical Middleware Microservice Orchestration and Fault-Tolerant Mechanism algorithms for Containerized Deployment

Technical Middleware Microservice Orchestration and Fault-To...

引用

IEEE international conference on Civil Aviation Safety and Information Technology (ICCASIT)

作者： Haoqi Dai Shaoguang Liu Bo Liu Zhongkai Fan Jinhe Wang Guangdong Provincial Key Laboratory of Digital Grid Technology Southern Power Grid Digital Grid Research Institute Co. Ltd. Guangzhou China

ISBN: (数字)9798350389418

ISBN: (纸本)9798350389425

Due to the containerized deployment environment, microservice orchestration requires coordination of multiple independently running services. this highly decoupled and distributed architecture increases the complexity of orchestration, and existing static resource allocation strategies are difficult to provide sufficient fault tolerance in the face of sudden failures. therefore, this article introduced a dynamic fault-tolerant scheduling algorithm based on Qlearning, which monitored service status in real-time, predicted potential faults, and dynamically adjusted resource allocation to improve system stability and fault tolerance. Firstly, microservices are modularized using the container orchestration tool Kubernetes, and containerization technology is utilized to encapsulate each service in a separate Pod for operation. Elastic allocation of resources can be achieved through Kubernetes’ automated scheduling mechanism, while efficient service communication and load balancing can be achieved through service mesh; Secondly, a dynamic faulttolerant scheduling algorithm based on Q-learning is introduced, combined with real-time monitoring data of CPU (Central processing Unit), memory, network traffic, etc., deployed in containers, to establish a fault prediction model. Finally, long short-term memory networks can be used to dynamically analyze and predict the load status and historical fault records of each service node, identify potential faults in real time, and automatically adjust resource allocation strategies based on the prediction results, reallocate service loads or start backup instances. the experimental results show that the Q-learningbased dynamic fault-tolerant scheduling algorithm effectively improves the system’s fault tolerance and stability. the analysis of fault recovery time showed that the recovery time for CPU overload, memory leakage, and network congestion was significantly reduced within 48 hours, to 7 seconds, 9 seconds, and 12 seconds, respec

关键词： Fault tolerance Machine learning algorithms Scheduling algorithms Heuristic algorithms Fault tolerant systems Microservice architectures Dynamic scheduling Stability analysis Real-time systems Resource management

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Massively parallel solution of the Lambert problem 19

Massively parallel solution of the Lambert problem

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19th international conference on Aviation and Cosmonautics, AviaSpace 2020

作者： Kravchenko, V.S. Ivanyukhin, A.V. Research Institute of Applied Mechanics and Electrodynamics Moscow Aviation Institute National Research University 5 Leningradskoye shosse Moscow125080 Russia Academy of Engineering Peoples Friendship University of Russia RUDN University 6 Miklukho-Maklaya street Moscow117198 Russia

this paper considers the possibility of massively parallel solution to the Lambert problem on graphics processing units. Several of the most popular solution algorithms were used for this problem. Software implementation of algorithms under consideration has been developed using Compute Unified Device Architecture technology that allows performing calculations on graphics processing units. A distinctive feature of this project is an attempt to use parallel programming within an iterative scheme. the developed algorithms have been tested on a number of typical tasks: contouring of Earth - Mars direct flight isolines and solution of the problem of a flight to a group of asteroids for the given start date and flight duration. For such tasks we give estimates of execution time and paralleling efficiency. © Published under licence by IOP Publishing Ltd.

关键词： Graphics processing unit

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A Novel Build-in-Test Method for the Multi-task Radar Warning Receiver Based on a parallel Radio Frequency Network 1

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9th international conference on Communications, Signal processing, and Systems, CSPS 2020

作者： Luo, Desi Li, Song Hui, Yang Zhou, Xu The 29Th Research Institute of China Electronics Technology Group Corporation Chengdu China

ISBN: (数字)9789811584114

ISBN: (纸本)9789811584107

A radar warning receiver (RWR) can detect and process radar signals to alarm radar threats in battlefields, and it has become an important sensor in the modern warfare. the multi-task RWR can improve the multi-signal processing capability and warning space, by adding processing hardware. As the amount of hardware increases, the reliability of whole system decreases. Multi-task RWR needs to conduct build-in-test before operation, to check the warning capability and locate the failed hardware. the traditional build-in-test schemes can test each sub-system of a single task independently with an external self-checking signal source. In this paper, we propose a novel build-in-test method for the multi-task RWR based on a parallel radio frequency (RF) network. the RF network makes the hardware of each sub-system as a backup for each other during the build-in-test. By utilizing the redundancy of parallel sub-systems, the joint build-in-test of the multi-task RWR can improve the accuracy without any additional RF signal detector. © 2021, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Testing

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Approximation algorithms for Two parallel Dedicated Machine Scheduling with Conflict Constraints 1

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15th Annual international conference on Combinatorial Optimization and Applications (COCOA)

作者： Zhang, An Zhang, Liang Chen, Yong Chen, Guangting Wang, Xing Hangzhou Dianzi Univ Dept Math Hangzhou 310018 Peoples R China Taizhou Univ Linhai 317000 Peoples R China

ISBN: (数字)9783030926816

ISBN: (纸本)9783030926816;9783030926809

We investigate two parallel dedicated machine scheduling with conflict constraints. the problem of minimizing the makespan has been shown to be NP-hard in the strong sense under the assumption that the processing sequence of jobs on one machine is given and fixed a priori. the problem without any fixed sequence was previously recognized as weakly NP-hard. In this paper, we first present a 9/5-approximation algorithm for the problem with a fixed sequence. then we show that the tight approximation ratios of the algorithm are 7/4 and 5/3 for two subproblems which remain strongly NP-hard. We also send an improved algorithm with approximation ratio 3 - root 2 approximate to 1.586 for one subproblem. Finally, we prove that the problem without any fixed sequence is actually strongly NP-hard, and design a 5/3-approximation algorithm to solve it.

关键词： parallel dedicated machines Conflict graph Approximation algorithm NP-hard

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parallel Approach to Sliding Window Sums 19th

Parallel Approach to Sliding Window Sums

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19th international conference on algorithms and architectures for parallel processing (ICA3PP)

作者： Snytsar, Roman Turakhia, Yatish Microsoft Corp One Microsoft Way Redmond WA 98052 USA Stanford Univ Stanford CA 94305 USA

ISBN: (纸本)9783030389611;9783030389604

Sliding window sums are widely used for string indexing, hashing, time series analysis and machine learning. New vector algorithms which utilize the advanced vector extension (AVX) instructions available on modern processors, or the parallel compute units on GPUs and FPGAs, would provide a significant performance boost. We develop a generic vectorized sliding sum algorithm with speedup for window size w and number of processors P is O(P/w) for a generic sliding sum. For a sum with commutative operator the speedup is improved to O(P/log(w)). Implementing the algorithm for the bioinformatics application of minimizer based k-mer table generation using AVX instructions, we obtain a speedup of over 5x.

关键词： Time series analysis

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A Framework for Designing Autonomous parallel Data Warehouses 19th

A Framework for Designing Autonomous Parallel Data Warehouse...

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19th international conference on algorithms and architectures for parallel processing (ICA3PP)

作者： Benkrid, Soumia Bellatreche, Ladjel Ecole Natl Super Informat ESI Algiers Algeria LIAS ISAE ENSMA Poitiers France

ISBN: (纸本)9783030389611;9783030389604

parallel data platforms are recognized as a key solution for processing analytical queries running on extremely large data warehouses (DWs). Deploying a DW on such platforms requires efficient data partitioning and allocation techniques. Most of these techniques assume a priori knowledge of workload. To deal with their evolution, reactive strategies are mainly used. the BI 2.0 requirements have put large batch and ad-hoc user queries at the center. Consequently, reactive-based solutions for deploying a DW in parallel platforms are not sufficient. Autonomous computing has emerged as a paradigm that allows digital objects managing themselves in accordance with high-level guidance by the means of proactive approaches. Being inspired by this paradigm, we propose in this paper, a proactive approach based on a query clustering model to deploying a DW over a parallel platform. the query clustering triggers partitioning and allocation processes by considering only evolved query groups. Intensive experiments were conducted to show the efficiency of our proposal.

关键词： Partitioning Allocation Common sub-expressions Utility maximization Autonomous system Workload clustering

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Am I Being Bullied on Social Media? An Ensemble Approach to Categorize Cyberbullying

Am I Being Bullied on Social Media? An Ensemble Approach to ...

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9th IEEE international conference on Big Data (IEEE BigData)

作者： Ahmed, Tasnim Kabir, Mohsinul Ivan, Shahriar Mahmud, Hasan Hasan, Kamrul Islamic Univ Technol Dept Comp Sci & Engn Dhaka Bangladesh

ISBN: (纸本)9781665439022

People can easily reveal their aggressive remarks on social media platforms using the anonymity it provides. During the COVID-19 pandemic, the usage of social media has been increased several times according to surveys and people are vulnerable to cyber attacks now more than ever. Prevention of cyberbullying needs careful monitoring and identification. Most of the existing works on cyberbullying detection employed traditional machine learning classifiers with handcrafted features, and deep learning-based models have made their way in this domain very recently. Categorizing cyberbullying based on traits is a complex task and needs contextual consideration. In this work, we have proposed a new approach to detect cyberbullying on social media platforms using a neural ensemble method of transformer-based architectures with attention mechanism. Our proposed architecture is trained on one balanced and one imbalanced dataset and outperforms the given ML and DNN baselines by a significant margin in both cases. We achieved an average F1-score of 95.59% for five classes and 90.65% for six classes on the Fine-Grained Cyberbullying Dataset (FGCD), and 87.28% on Twitter parsed dataset. Our in-depth results provide great insights into the effectiveness of transformer-based models in cyberbullying detection and paves the way for future researches to combat this serious online issue. We have released our models and code.(1)

关键词： Cyberbullying Detection Social Media Data Mining Natural Language processing Transformers Ensemble Learning

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Proceedings of the 11th Workshop on parallel Programming and Run-Time Management Techniques for Many-Core architectures / 9th Workshop on Design Tools and architectures for Multicore Embedded Computing Platforms, PARMA-DITAM 2020

Proceedings of the 11th Workshop on Parallel Programming and...

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8th international Symposium on Highly-Efficient Accelerators and Reconfigurable Technologies, HEART 2017

ISBN: (纸本)9781450375450

the proceedings contain 5 papers. the topics discussed include: sparse matrix-dense matrix multiplication on heterogeneous CPU+FPGA embedded system;run-time power modeling in embedded GPUs with dynamic voltage and frequency scaling;fault-tolerant online scheduling algorithms for CubeSats;an OpenMP parallel genetic algorithm for design space exploration of heterogeneous multi-processor embedded systems;and automated precision tuning in activity classification systems: a case study.

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An OpenMP parallel Genetic Algorithm for Design Space Exploration of Heterogeneous Multi-processor Embedded Systems 2020

An OpenMP Parallel Genetic Algorithm for Design Space Explor...

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11th Workshop on parallel Programming and Run-Time Management Techniques for Many-Core architectures / 9th Workshop on Design Tools and architectures for Multicore Embedded Computing Platforms, PARMA-DITAM 2020

作者： Muttillo, Vittoriano Giammatteo, Paolo Fiorilli, Giuseppe Pomante, Luigi University of L’Aquila L’Aquila Italy

ISBN: (纸本)9781450375450

Heterogeneous multiprocessor platforms are becoming widespread in the embedded system domain, mainly for the opportunity to improve timing performance and to minimize energy/power consumption and costs. therefore, when using such platforms, it is important to adopt a Design Space Exploration (DSE) strategy that considers compromises among different objectives. Existing DSE approaches are generally based on evolutionary algorithms to solve Multi-Objective Optimization Problems (MOOPs) by minimizing a linear combination of weighted cost functions (i.e., Weighted Sum Method, WSM). In this way, the main issues are related to reduce timing execution while trying to improve the evolutionary algorithm performance, introducing strategies that attempt to bring better solutions. Code parallelization is one of the most used approaches in this field, but no standard methods have been released since different aspects could affect the performance. this approach leads to exploit parallel and distributed processing elements in order to implement evolutionary algorithms. In the latter case, if we consider genetic algorithms, it is possible to talk about parallel Genetic algorithms (PGA). Considering this context, this paper focuses on DSE for heterogeneous multi-processor embedded systems and introduces an improvement that reduces execution time using parallel programming languages (i.e., OpenMP) inside the main genetic algorithm approach, while trying to lead to better partitioning solutions. the descriptions of the adopted DSE activities and the OpenMP implementation, validated by means of a case study, represent the core of the paper. © 2020 Association for Computing Machinery.

关键词： Multiobjective optimization

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parallel Shift-Invert Spectrum Slicing on Distributed architectures with GPU Accelerators 20

Parallel Shift-Invert Spectrum Slicing on Distributed Archit...

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49th international conference on parallel processing (ICPP)

作者： Williams-Young, David B. Yang, Chao Lawrence Berkeley Natl Lab Computat Res Div Berkeley CA 94720 USA

ISBN: (纸本)9781450388160

the solution of large scale eigenvalue problems (EVP) is often the computational bottleneck for many scientific and engineering applications. Traditional eigensolvers, such as direct (e.g. ScaLAPACK) and Krylov subspace (e.g. Lanczos) methods, have struggled in achieving high scalability on large computing resources due to communication and synchronization bottlenecks which are inherent in their implementation. this includes a difficulty in developing well-performing ports of these algorithms to architectures which rely on the use of accelerators, such as graphics processing units (GPU), for the majority of their floating point operations. Recently, there has been significant research into the development of eigensolvers based on spectrum slicing, in particular shift-invert spectrum slicing, to alleviate the communication and synchronization bottlenecks of traditional eigensolvers. In general, spectrum slicing trades the global EVP for many smaller, independent EVPs which may be combined to assemble some desired subset of the entire eigenspectrum. the result is a method which utilizes more floating point operations than traditional eigensolvers, but in a way which allows for the expression of massive concurrency leading to an overall improvement in time-to-solution on large computing resources. In this work, we will examine the performance of parallel shift-invert spectrum slicing on modern GPU clusters using state-of-the-art linear algebra software.

关键词： Graphics processing unit

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