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

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Application Virtualization: An Agent Encapsulation of software in Virtual Machines to Archive the Execution Performance in Hosts 19

Application Virtualization: An Agent Encapsulation of Softwa...

引用

19th IEEE international symposium on parallel and distributed Processing with Applications (IEEE ISPA)

作者： Liang, Yifan Dai, Hongjun Shandong Univ Sch Software Jinan Peoples R China

ISBN: (纸本)9781665435741

Virtualization is now a key technology for increasing the utilization of physical hardware, and many software programs are benefiting from it. Virtual machine software has become more and more demanding in terms of virtual machine performance. Nowadays, the performance improvement of software inside a virtual machine comes from it of the virtual machine hardware, which is far less than the performance improvement of the same software on the physical machine. We propose Application Virtualization to improve the execution of virtual machine software inside the virtual machine. It can be implemented on existing virtualization platforms to simplify the deployment difficulty and execution efficiency of software inside virtual machines and providing a common way to invoke host software.

关键词： para-virtualization application virtualization inter-domain communication

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Optimizing the Response Time for ROS Tasks in Multi-Core Processors 27

Optimizing the Response Time for ROS Tasks in Multi-Core Pro...

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27th IEEE/ACM international symposium on distributed Simulation and Real Time Applications, DS-RT 2023

作者： Kim, Sunho Park, Hayeon Lee, Chang-Gun Seoul National University Dept. of Mechanical Engineering Seoul Korea Republic of Seoul National University Dept. of Computer Science Seoul Korea Republic of

ISBN: (纸本)9798350337846

This paper presents methods to optimize the response time of ROS (Robot Operating System), a widely utilized open-source meta-operating system in robotic software development. Despite its popularity, ROS lacks real-time capabilities, making it unsuitable for real-time control and difficult to use in embedded systems. Recently, DAG (Directed Acyclic Graph) task scheduling algorithms have gained much attention, but they are challenging to apply in the current design of ROS. In this work, we analyze that there are three major challenges in ROS;(i) misalignment delay, (ii) message delivery mechanism using TCP/IP, and (iii) multiple overlapping instances of a single task. We first calculate the new response time bound considering misalignment delay and propose an optimization technique using it to solve the first problem. Furthermore, we address the remaining challenges by assigning priority to the nodes of the DAG and ksoftirqd processes. Our experiments using random tasks show significant improvement, outperforming the state-of-art methods. In addition, our methods are validated through testing autonomous driving software on embedded systems, proving their real-world applicability. © 2023 IEEE.

关键词： Multitasking

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software Defect Classification and Analysis Study

Software Defect Classification and Analysis Study

引用

Information Science, parallel and distributed systems (ISPDS), international Conference on

作者： Liyuan Zheng Yang Xie Boyuan Hou Xin Xie Institute of Computer Application China Academy of Engineering Physics Mianyang China

ISBN: (数字)9798350352719

ISBN: (纸本)9798350352726

This study proposes a set of improved defect categorization criteria and analysis strategies based on a synthesis of a variety of commonly used software defect categorization methods, combined with the actual software development and testing process. By exploring the defect analysis process, this paper discusses the application of this standard in practice. Finally, basic methods and processes are proposed for software defect prevention, providing theoretical and practical guidance for quality management in the software development process.

关键词： Productivity Prevention and mitigation Standards organizations Organizations Reliability theory software software reliability

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A Scheduling Algorithm for Hyperledger Fabric Based on Transaction Batch Processing

A Scheduling Algorithm for Hyperledger Fabric Based on Trans...

引用

international symposium on parallel and distributed Computing

作者： Junyu Jia Ou Wu Shanshan Li Rufei Ma He Zhang Anhui Normal University China State Key Laboratory of Novel Software Technology Nanjing University China Software Institute Nanjing University China Department of Basic Courses The PLA Army Engineering University

ISBN: (数字)9798350369199

ISBN: (纸本)9798350369205

Hyperledger Fabric (Fabric for short), is a consortium blockchain platform that adopts the smart contract paradigm and provides complete operational functions. Although it has become the system with the highest throughput among open source blockchain systems, its performance cannot meet the needs of industrial-grade application scenarios. To further expand the application scenarios of blockchain, this paper proposes a Transaction Batch Processing Scheduling (TBPS) algorithm for multi-channel Fabric networks based on Lyapunov optimization theory. The algorithm maximizes the consensus efficiency of the system while ensuring the minimum transaction accumulation, and provides stability conditions and optimal performance for the system under transaction batch processing. Finally, we built a blockchain network of Fabric’s latest stable version v 2.0 via the cloud platform, providing an order of magnitude of algorithmic parameters by testing transaction processing rates. To simulate the distribution of performance indicators such as transaction delay, system transaction accumulation and average transaction processing rate under different impact factors, and verify the effectiveness of the proposed TBPS algorithm.

关键词： distributed ledger Batch production systems Throughput Fabrics Stability analysis Blockchains Classification algorithms Thermal stability Optimization Testing

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EduPar 2024 Keynote Speaker

EduPar 2024 Keynote Speaker

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

作者： Charles E. Leiserson MIT Department of Electrical Engineering and Computer Science MIT Computer Science and Artificial Intelligence Laboratory

ISBN: (数字)9798350364606

ISBN: (纸本)9798350364613

Aside from pure intellectual interest, why do we teach our students parallel computing? Most people would agree that the primary goal is to produce greater application performance. Yet students frequently parallelize code only to discover that it runs disappointingly slower because they don't understand performance. To exploit parallelism effectively, it must operate synergistically with a host of other techniques, including caching, vectorization, algorithms, bit tricks, loop unrolling, using compiler switches, tailoring code to the architecture, exploiting sparsity, changing data representation, metaprogramming, etc. software performance engineering, which encompasses these techniques, is the science and art of making code run fast or otherwise limiting its consumption of resources, such as energy, memory footprint, network utilization, response time, etc. In this talk, I will argue that the end of Moore's Law makes software performance engineering a critical skill for our students to learn.

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Renewable Energy Assessment: A Comparative Study of Saudi Arabia and Greensboro-NC 6

Renewable Energy Assessment: A Comparative Study of Saudi Ar...

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6th international symposium on Advanced Electrical and Communication Technologies, ISAECT 2024

作者： Darwish, Hiba Alhuwaidi, Sadiq Alhmoud, Issa W. Alsumady, Mohammed Gokaraju, Balakrishna North Carolina Agricultural and Technical State University Computational Data Science and Engineering Greensboro United States Prince Mohammad Bin Fahd University Department of Electrical Engineering Al-Khobar Saudi Arabia Yarmouk University Department of Electronics Engineering Irbid Jordan

ISBN: (纸本)9798331529987

This paper comprehensively assesses wind and solar energy potential in the Kingdom of Saudi Arabia (KSA), focusing on five strategically selected locations: Al-Ahsa, Riyadh, Rafha, Tabuk, and Unayzah. The analysis was extended, and a comparison was made between the results of the investigated locations in KSA and the city of Greensboro North Carolina State in USA. The study aims to estimate the amount of energy that can be extracted from wind and solar resources, leveraging advance d computational tools for precise evaluation. The "Distribution Fitter"app in MATLAB was utilized to fit the parameters of the used probability density functions PDFs. In parallel, the RETScreen software was utilized to estimate the annual extractable energy from solar photovoltaic (PV) systems, offering a reliable simulation of solar irradiance and system performance. Greensboro stands out as the most promising site for wind energy extraction with an annual amount of 21,022.02 MWh by 10 Vestas turbines, while Al-Ahsa demonstrates the highest potential for solar energy harvesting with an annual estimated amount of 257.426 MWh by a 100 kW PV system. This dual-resource assessment highlights the regional variability in renewable energy potential across KSA, emphasizing the importance of site-specific analysis for optimal energy resource utilization. The results serve as a valuable reference for policymakers and stakeholders in the renewable energy sector, guiding future investments and development plans toward sustainable energy solutions in the region. © 2024 IEEE.

关键词： Clean energy

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Upside down: an open-source motion platform for highly dynamic movement 56

Upside down: an open-source motion platform for highly dynam...

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56th international symposium on Robotics, ISR Europe 2023

作者： Pradhan, Nayan Man Singh Frank, Patrick Mo, An Badri-Spröwitz, Alexander Dynamic Locomotion Group Max Planck Institute for Intelligent Systems Stuttgart Germany Department of Mechanical Engineering KU Leuven Belgium

ISBN: (纸本)9783800761418

parallel robots are capable of high-speed manipulation and have become essential tools in the industry. The proximal placement of their motors and the low weight of their end effectors make them ideal for generating highly dynamic motion. Therefore, we can adopt parallel robots for motion platform designs if end effector loads are low. Traditional motion platforms can be large and powerful to generate multiple g accelerations. However, these designs tend to be expensive and large. Similar but smaller motion platforms feature a small work range with reduced degrees of freedom (DoFs) and a limited payload. Here we seek a medium-sized, affordable parallel robot capable of powerful, high-speed 6-DoF motion in a comparably large workspace. We explore the concept of a quadruped robot flipped upside-down, with the motion platform fixed between its feet. In particular, we exploit the high-power dynamic brushless actuation and the four-leg redundancy when moving the motion platform. We characterize the resulting motion platform by tracking sinusoidal and circular trajectories with varying loads. Dynamic motions in 6 DoFs up to 2 Hz and ± 20 mm amplitude are possible when moving a mass of 1.2 kg. For single-axis end-effector translations, we demonstrate up to 10 Hz and ± 10 mm amplitude for loads of 0.3 kg. The motion platform can be replicated easily by 3D printing and with off-the-shelf components. All hardware designs and custom-written software are open-source available. © VDE VERLAG GMBH Berlin Offenbach.

关键词： motion platform open source parallel robot quadruped

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Reducing Data Bottlenecks in distributed, Heterogeneous Neural Networks 17

Reducing Data Bottlenecks in Distributed, Heterogeneous Neur...

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17th IEEE international symposium on Embedded Multicore/Many-core systems-on-Chip, MCSoC 2024

作者： Lin, Ruhai Zhu, Rui-Jie Eshraghian, Jason K. Uc Santa Cruz Dept. of Electrical and Computer Engineering Santa CruzCA United States

ISBN: (纸本)9798331530471

The rapid advancement of embedded multicore and many-core systems has revolutionized computing, enabling the development of high-performance, energy-efficient solutions for a wide range of applications. As models scale up in size, data movement is increasingly the bottleneck to performance. This movement of data can exist between processor and memory, or between cores and chips. This paper investigates the impact of bottleneck size, in terms of inter-chip data traffic, on the performance of deep learning models in embedded multicore and many-core systems. We conduct a systematic analysis of the relationship between bottleneck size, computational resource utilization, and model accuracy. We apply a hardware-software co-design methodology where data bottlenecks are replaced with extremely narrow layers to reduce the amount of data traffic. In effect, time-multiplexing of signals is replaced by learnable embeddings that reduce the demands on chip IOs. Our experiments on the CIFAR100 dataset demonstrate that the classification accuracy generally decreases as the bottleneck ratio increases, with shallower models experiencing a more significant drop compared to deeper models. Hardware-side evaluation reveals that higher bottleneck ratios lead to substantial reductions in data transfer volume across the layers of the neural network. Through this research, we can determine the trade-off between data transfer volume and model performance, enabling the identification of a balanced point that achieves good performance while minimizing data transfer volume. This characteristic allows for the development of efficient models that are well-suited for resource-constrained environments. © 2024 IEEE.

关键词： Deep learning

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A Moving Target Defense Approach for the distributed Dynamic Network 21

A Moving Target Defense Approach for the Distributed Dynamic...

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21st IEEE international symposium on parallel and distributed Processing with Applications, 13th IEEE international Conference on Big Data and Cloud Computing, 16th IEEE international Conference on Social Computing and Networking and 13th international Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Zhang, Lin Guo, Yunchuan Leng, Siyuan Li, Zifu Li, Fenghua Fang, Liang Institute of Information Engineering Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences School of Cyber Security Beijing China

ISBN: (纸本)9798350329223

The distributed dynamic network is vulnerable to scanning attacks due to the openness of wireless channels. Traditional defense systems tend to be passive and exhibit delayed responses. A moving target defense approach, namely distributed Network Address Shuffling (DNAS), is proposed to thwart attackers' network scanning through the shuffling of network addresses. To resolve address conflicts resulting from this shuffling, DNAS employs a dynamic diffusion method of allocated addresses before the shuffling process to reduce the probability of conflict generation, and utilizes a passive detection based conflict elimination algorithm after the shuffling process to eliminate any generated conflicts. To select low-risk addresses, DNAS leverages an artificial feature selection based Fully Connected Neural Network (FCNN) to recognize the attacker's scanning policy, and identifies low-risk addresses based on the scanning range of the policy. Empirical experiments and theoretical analysis indicate that DNAS significantly reduces the probability of address conflict generation at a minimal cost. It effectively eliminates all generated address conflicts within an average conflict resolution time of less than 500ms. Furthermore, DNAS exhibits an accuracy of 99.45% in recognizing scanning policies, surpassing pseudorandom address hopping in diminishing the success rate of sequential, local random, and mixed scanning. © 2023 IEEE.

关键词： Network security

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A Correlation And Order-Aware Rule Learning Method For Knowledge Graph Reasoning 29

A Correlation And Order-Aware Rule Learning Method For Knowl...

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29th IEEE international Conference on parallel and distributed systems, ICPADS 2023

作者： He, Yuefeng He, Yang Zheng, Xu Hui, Bei Tian, Bin University of Electronic Science and Technology of China Shenzhen Institute for Advanced Study Shenzhen China University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu China University of Electronic Science and Technology of China School of Information and Software Engineering Chengdu China Naval University of Engineering Wuhan China

ISBN: (纸本)9798350330717

Mining high-quality logical rules is crucial as they can provide beneficial interpretability for predictions. Recent methods that incorporate logical rules into learning tasks have been proven to yield high-quality logical rules successfully. However, existing methods either rely on the rule instances observed to support rule mining, or simply embed the rule head and the rule body to learn from them. Additionally, they can not fully utilize the rich semantic information contained in logical rules and overlook the intrinsic correlations between all relations within the domain. In this paper, we propose a model called Correlation and order-Aware Rule Learning (CARL) that captures deeper semantic information in rules by allowing relations to be co-aware of each other and paying attention to logical sequence sensitivity. CARL utilizes semantic consistency between the rule body and rule head as its learning objective, continuously introducing more semantic information and logically simplifying the rule body while considering logical sequence sensitivity. We explored the internal correlations between domain relations and used the thought of knowledge distillation to simplify modules so that relations in CARL can share or perceive each other's information or state efficiently. Experiments on link prediction tasks have demonstrated that CARL can learn higher-quality rules and yield state-of-the-art results on four popular public datasets. https://***/burning5112/CARL © 2023 IEEE.

关键词： knowledge graph reasoning rule learning

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