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A parallel Partial Merge Repair Algorithm for Multi-block Failures for Erasure Storage systems

A Parallel Partial Merge Repair Algorithm for Multi-block Fa...

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international symposium on parallel and distributed Processing (IPDPS)

作者： Shuaipeng Zhang Shiyi Li Chentao Wu Ruobin Wu Saiqin Long Wen Xia Harbin Institute of Technology Shenzhen Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies Wuhan National Laboratory for Optoelectronics Shanghai Jiao Tong University Jinan University

ISBN: (数字)9798350387117

ISBN: (纸本)9798350387124

In order to achieve high availability and low storage costs in distributed storage systems, erasure code is widely used instead of replication. Compared to replication, erasure code can reduce storage costs, but also brings higher repair costs. There are currently many repair algorithms to reduce the block reconstruction time of single block failure. However, applying the existing methods to multi-block failures may lead to unbalanced network traffic, unnecessary network transfers, and network congestion at data collection node during the repair process, which can not make full use of the bandwidth between *** solve this problem, we propose a novel repair algorithm called Partial Merge Repair (PMR) for multi-block failures, which is a scheduling algorithm that considers network load between nodes and combines multiple failed blocks to recover together. It first divides all surviving nodes into different groups, and then the data collection nodes within the group collect the data needed to repair multiple blocks through cross merging. Finally, the data collection node sends the collected blocks to the repair node to complete the repair. Our study presents a formal definition and proof of network transfer time in the modeled repair process of PMR, highlighting its superior efficiency compared to existing methods in homogeneous *** implement a prototype of PMR to evaluate its performance. The experimental results indicate that compared to existing repair technologies, PMR improves repair throughput by 28%-256% for various scenes.

关键词： Costs Codes Scheduling algorithms Bandwidth Telecommunication traffic Maintenance engineering Data collection

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Efficient Storage and Retrieval of Similar Data in Edge Computing systems

Efficient Storage and Retrieval of Similar Data in Edge Comp...

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international Conference on parallel and distributed systems (ICPADS)

作者： Yuanfeng Liu Junjie Xie Hanlong Liao Sheng Chen Xiulong Liu Deke Guo College of Intelligence and Computing Tianjin University Tianjin China Institute of Systems Engineering AMS Beijing China Science and Technology on Information Systems Engineering Laboratory National University of Defense Technology Changsha China

Edge computing is migrating services from remote clouds to the network edge, where a vast amount of data is also flowing into edge nodes. In this context, the Edge Data-Sharing System (EDSS) enhances service quality by enabling edge nodes to cooperate. However, the EDSS is suitable for precise search and faces the existing high overhead when many users retrieve similar data. To solve the obstacle, this paper proposes a similarity-based edge storage system, SESS, which leverages the software-defined edge network to realize efficient storage and retrieval of similarity data. We first design RealminHash, a core module of SESS, for efficient signature and and index for each data. Then, SESS calculates the storage strategy based on the similarity between data. Importantly, SESS adjusts this strategy using periodic network information to ensure load balancing. Experimental results demonstrate that SESS realizes the nearest-neighbor storage while maintaining load balancing. SESS outperforms the well-known k-means and spectral clustering methods in terms of accuracy and latency and supports millisecond similar queries.

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Design of VLC-Enabled Hybrid Data Center Network and Routing Algorithm

Design of VLC-Enabled Hybrid Data Center Network and Routing...

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international symposium on parallel and distributed Processing with Applications, ISPA

作者： Linyu Yang Xiaoyu Du Yujing Wang Shuaiqi Liu School of Computer and Information Engineering Henan University Kaifeng China Henan Engineering Research Center for Industrial Internet of Things Zhengzhou China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

Data centers have become the digital backbone of modern society, and the deployment of data center networks has evolved toward massive scale and multipath. However, existing designs still face challenges in terms of ease of deployment and plug-and-play. To address these issues, this paper proposes a hybrid data center network SHCN that supports visible light communication (VLC). First, all racks are organized into a wireless small-world network using VLC links such that multiple paths exist between any two racks for communication. Second, in order to seamlessly integrate the wired network with the wireless network, the small-world network is optimized by incorporating the characteristics of the wired network. To address the line-of-sight limitation problem of VLC links, a transceiver space layout method is proposed to avoid blocking of VLC links. In addition, based on the characteristics of SHCN structure, a hybrid unicast routing algorithm is designed to effectively reduce the number of longer routing paths in the network. Comprehensive evaluation shows that compared with the original wired structure HCN, SHCN has rich path diversity, higher connectivity and lower average path length, and can perform well in data centers.

关键词： Data centers Fault tolerance Unicast Wireless networks Layout Fault tolerant systems Line-of-sight propagation Routing Transceivers Visible light communication

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Nonlinear Control of Crane systems Based on Intelligence Computing of Disturbance Observer Under Mismatched Disturbance

Nonlinear Control of Crane Systems Based on Intelligence Com...

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international symposium on parallel and distributed Processing with Applications, ISPA

作者： Tianlei Wang Yiyan Wang Meng Xu Jiajie Tian Jingling Zhang Zhiyong Hong School of Electronic and Information Engineering Wuyi University Jiangmen China Jiangmen Key Laboratory of Kejie Semiconductor Bonding Technology and Control System Jiangmen China School of Mechanical and Automation Engineering Wuyi University Jiangmen China Guangdong Kejie Technology Co. Ltd Jiangmen China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

A control method based on disturbance observer is proposed to address the positioning drift issue of the gantry crane under unmatched disturbances, aiming at precise positioning of the trolley and effective payload swing angle attenuation in a variable-length two-dimensional lifting system. The control scheme comprises a combination of a proportional-derivative controller and a disturbance observer. Firstly, the design of the coupling function in this paper is based on the observation of the natural characteristics of the dynamical model. It cleverly designs the coupling function, which not only helps to effectively reduce the swing angle but also prevents the problem of positioning drift under non-matching disturbances, subsequently, design a controller by integrating intelligent computing with control theory. Secondly, the designed disturbance observer observes and compensates for the system output to achieve disturbance suppression. Thirdly, a thorough stability analysis has been conducted to demonstrate that the proposed controller satisfies the desired conditions. Finally, simulation results illustrate that the pro-posed method success-fully addresses the limitations of existing methods and exhibits superior performance and robustness.

关键词： Couplings Cranes Computational modeling Simulation Attenuation Disturbance observers Stability analysis Robustness Mathematical models Payloads

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AnyQ: An Evaluation Framework for Massively-parallel Queue Algorithms

AnyQ: An Evaluation Framework for Massively-Parallel Queue A...

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international symposium on parallel and distributed Processing (IPDPS)

作者： Michael Kenzel Stefan Lemme Richard Membarth Matthias Kurtenacker Hugo Devillers Markus Steinberger Philipp Slusallek Saarland Informatics Campus Deutsches Forschungszentrum für Künstliche Intelligenz (DFKI) Graz University of Technology Technische Hochschule Ingolstadt (THI) Research Institute AImotion Bavaria Saarland Informatics Campus Saarland University

Concurrent queue algorithms have been subject to extensive research. However, the target hardware and evaluation methodology on which the published results for any two given concurrent queue algorithms are based often share only minimal overlap. A meaningful comparison is, thus, exceedingly difficult. With the continuing trend towards more and more heterogeneous systems, it is becoming more and more important to not only evaluate and compare novel and existing queue algorithms across a wider range of target architectures, but to also be able to continuously re-evaluate queue algorithms in light of novel architectures and *** address this need, we present AnyQ, an evaluation framework for concurrent queue algorithms. We design a set of programming abstractions that enable the mapping of concurrent queue algorithms and benchmarks to a wide variety of target architectures. We demonstrate the effectiveness of these abstractions by showing that a queue algorithm expressed in a portable, high-level manner can achieve performance comparable to hand-crafted implementations. We design a system for testing and benchmarking queue algorithms. Using the developed framework, we investigate concurrent queue algorithm performance across a range of both CPU as well as GPU architectures. In hopes that it may serve the community as a starting point for building a common repository of concurrent queue algorithms as well as a base for future research, all code and data is made available as open source software at https://***/anyq.

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Constructions of Binary MDS Array Codes with Optimal Cooperative Repair Bandwidth

Constructions of Binary MDS Array Codes with Optimal Coopera...

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IEEE international symposium on Information Theory

作者： Lei Li Xinchun Yu Chenhao Ying Liang Chen Yuanyuan Dong Yuan Luo Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Institute of Data and Information Tsinghua University Shenzhen International Graduate School Shenzhen China Alibaba Group Hangzhou China

ISBN: (数字)9798350382846

ISBN: (纸本)9798350382853

Erasure codes are widely implemented in distributed storage systems to provide high fault tolerance with small storage overhead. Maximum distance separable codes are an common choice as they achieve the optimal tradeoff between fault tolerance and storage overhead. In this paper, we focus on the repair of multiple erasures of binary MDS array codes. Specifically, we present constructions of binary MDS array codes with optimal cooperative repair bandwidth by stacking multiple Blaum-Roth code instances whose “evaluation points” are judiciously designed. The constructed array codes with length $n$ and dimension $k$ can achieve the optimal cooperative repair bandwidth for $2\leq h\leq n-k$ and $k+1\leq d\leq n-h$ where $h$ and $d$ are the numbers of failed nodes and helper nodes, respectively. As the codes are constructed on a special polynomial ring over binary field, computation operations involved in nodes repair and file reconstruction for these codes are only XORs and cyclic shifts. Moreover, due to the inherent parallel structure of the codes, both the encoding and decoding procedures can be finished in parallel, speeding up the computing process.

关键词： Fault tolerance Codes Stacking Fault tolerant systems Bandwidth Maintenance engineering Polynomials

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Facilitating Data Discovery for Large-scale Science Facilities using Knowledge Networks 35

Facilitating Data Discovery for Large-scale Science Faciliti...

引用

35th IEEE international parallel and distributed Processing symposium (IPDPS)

作者： Qin, Yubo Rodero, Ivan Parashar, Manish Rutgers State Univ Rutgers Discovery Informat Inst New Brunswick NJ 08854 USA Univ Utah Sci Comp Imaging Inst Salt Lake City UT USA

ISBN: (纸本)9781665440660

Large-scale multiuser scientific facilities, such as geographically distributed observatories, remote instruments, and experimental platforms, represent some of the largest national investments and can enable dramatic advances across many areas of science. Recent examples of such advances include the detection of gravitational waves and the imaging of a black hole's event horizon. However, as the number of such facilities and their users grow. along with the complexity, diversity, and volumes of their data products, finding and accessing relevant data is becoming increasingly challenging, limiting the potential impact of facilities. These challenges are further amplified as scientists and application workflows increasingly try to integrate facilities' data from diverse domains. In this paper, we leverage concepts underlying recommender systems, which are extremely effective in e-commerce, to address these data-discovery and data-access challenges for large-scale distributed scientific facilities. We first analyze data from facilities and identify and model user-query patterns in terms of facility location and spatial localities, domain-specific data models, and user associations. We then use this analysis to generate a knowledge graph and develop the collaborative knowledge-aware graph attention network (CKAT) recommendation model, which leverages graph neural networks (GNNs) to explicitly encode the collaborative signals through propagation and combine them with knowledge associations. Moreover, we integrate a knowledge-aware neural attention mechanism to enable the CKAT to pay more attention to key information while reducing irrelevant noise, thereby increasing the accuracy of the recommendations. We apply the proposed model on two real-world facility datasets and empirically demonstrate that the CKAT can effectively facilitate data discovery, significantly outperforming several compelling state-of-the-art baseline models.

关键词： Knowledge engineering Analytical models Observatories Limiting Instruments Collaboration Data models

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Machine Learning for CUDA+MPI Design Rules 36

Machine Learning for CUDA+MPI Design Rules

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36th IEEE international parallel and distributed Processing symposium Workshops, IPDPSW 2022

作者： Pearson, Carl Javeed, Aurya Devine, Karen Sandia National Laboratories AlbuquerqueNM United States

ISBN: (纸本)9781665497473

We present a new strategy for automatically exploring the design space of key CUDA + MPI programs and providing design rules that discriminate slow from fast implementations. In such programs, the order of operations (e.g., G PU kernels, MPI communication) and assignment of operations to resources (e.g., G PU streams) makes the space of possible designs enormous. systems experts have the task of redesigning and reoptimizing these programs to effectively utilize each new platform. This work provides a prototype tool to reduce that burden. In our approach, a directed acyclic graph of CUDA and MPI operations defines the design space for the program. Monte-Carlo tree search discovers regions of the design space that have large impact on the program's performance. A sequence-to-vector transformation defines features for each explored im-plementation, and each implementation is assigned a class label according to its relative performance. A decision tree is trained on the features and labels to produce design rules for each class;these rules can be used by systems experts to guide their implementations. We demonstrate our strategy using a key kernel from scientific computing - sparse-matrix vector multiplication - on a platform with multiple MPI ranks and GPU streams. © 2022 IEEE.

关键词： parallel programming

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BachLedger: Orchestrating parallel Execution with Dynamic Dependency Detection and Seamless Scheduling

BachLedger: Orchestrating Parallel Execution with Dynamic De...

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international Conference on parallel and distributed systems (ICPADS)

作者： Yi Yang Guangyong Shang Guangpeng Qi Zhen Ma Yaxiong Liu Jiazhou Tian Aocheng Duan Meng Zhang Jingying Li Xuan Ding School of Software Tsinghua University Beijing China Inspur Yunzhou Industrial Internet Co. Ltd Jinan Shandong China School of Cyber Engineering Xidian University Xi’an Shaanxi China

ISBN: (数字)9798331515966

ISBN: (纸本)9798331515973

Blockchain technology inherently necessitates redundant computation to achieve consensus among untrusted parties because of its fundamental threat model. This requirement, however, compromises system performance and impedes the widespread adoption of blockchain. To leverage existing physical resources, current research on high-performance consortium blockchain algorithms and architectures frequently employs cluster-node architectures to expand the parallel processing capability of traditional single physical nodes. Our investigation reveals a significant trend as the parallel capability of individual nodes improves. The idle time caused by synchronization of all transactions within each block, previously considered negligible, has become increasingly significant. To address this, we present BachLedger, which implements Seamless Scheduling to fully utilize inter-block thread idle time, thereby augmenting system resource utilization and achieving overall performance improvements. Our experimental results demonstrate that our algorithm surpasses current state-of-the-art (SOTA) performance levels in high-performance consortium blockchains and effectively resolves the aforementioned synchronization issue. Furthermore, this scheduling algorithm offers enhanced scalability for BachLedger, positioning it as a promising solution for future blockchain implementations.

关键词： Threat modeling Scheduling algorithms System performance Scalability Computer architecture parallel processing Dynamic scheduling Blockchains Synchronization Resource management

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Visualization Analysis of Artificial Intelligence Applications in Rural Areas Based on Citespace

Visualization Analysis of Artificial Intelligence Applicatio...

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

作者： Qian Zhang Jing Zhao Liping Xia International Business School Shaanxi Normal University Xi’an China School of Economics and Management Changji University Changji China School of Information Engineering Changji University Changji China

ISBN: (数字)9798350352719

ISBN: (纸本)9798350352726

With the rapid development of artificial intelligence, research on its application in rural development is increasing. This paper focuses on the literature on artificial intelligence empowering rural and agricultural development from the Web of Science core from 2014 to 2023. Using CiteSpace software, it conducts a visualization analysis of the literature over the past decade, examining the current status, hotpots, and trends of research from six aspects: publication quantity, disciplinary distribution, institutions, countries and regions distribution, research hotpots, and trends. Conclusion: Regarding the current status, there is rich international research on the application of artificial intelligence in rural areas, with an overall increasing trend in research quantity since 2018. Collaboration networks among institutions have begun to form, with China, the United States, and India conducting more research with higher impact. Regarding research hotpots, machine learning and deep learning are popular application technologies, with digital agriculture and precision agriculture being the main research objects over the past decade. Regarding research trends, integrating artificial intelligence technology with smart rural development and smart agriculture will further deepen.

关键词： Smart agriculture Precision agriculture Deep learning Visualization Information science Bibliometrics Collaboration

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