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检索条件"任意字段=International Symposium on Databases in Parallel and Distributed Systems"

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P-RECS 2022 - Proceedings of the 5th international Workshop on Practical Reproducible Evaluation of Computer systems, co-located with HPDC 2022

P-RECS 2022 - Proceedings of the 5th International Workshop ...

引用

5th international Workshop on Practical Reproducible Evaluation of systems, P-RECS 2022, co-located with The 31st international symposium on High-Performance parallel and distributed Computing, HPDC 2022

The proceedings contain 3 papers. The topics discussed include: expanding the scope of artifact evaluation at HPC conferences: experience of SC21;reproducible experiments for internet systems;and managing randomness t...

ISBN: (纸本)9781450393133

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Inverse Relational Reasoning Based on 3D-CRN Direction Relation Model

Inverse Relational Reasoning Based on 3D-CRN Direction Relat...

引用

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

作者： Zhenxi Fang Weiguang Liu Miao Wang Hao Tang Department of Computer Science Zhongyuan University of Technology Zhengzhou China College of Computer Science Henan Institute of Engineering Zhengzhou China

ISBN: (数字)9798350352719

ISBN: (纸本)9798350352726

In recent years, although a number of spatial directional relation models have been proposed, the reasoning ability of spatial directional relations is limited due to the inherent defects of some models and the weak research on the corresponding reasoning techniques, which reduces the usefulness of the models to a certain extent. Based on the 3D-CRN directional relation expression and inference model, combining three-dimensional algebra and qualitative coordinates, establishing equivalent links, an automatic qualitative inference algorithm for the inverse relation between principal directional relations is proposed, which gets rid of the dependence on manual inference tables, greatly improves the operational efficiency, and increases the practicality of the model. The results of theoretical analysis and example verification show that the algorithm effectively improves the accuracy of reasoning and reduces the time complexity of reasoning.

关键词： Solid modeling Analytical models Accuracy Inverse problems Manuals Cognition Spatial databases

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Sparse Matrix-Vector Multiplication Cache Performance Evaluation and Design Exploration 29

Sparse Matrix-Vector Multiplication Cache Performance Evalua...

引用

29th international symposium on the Modeling, Analysis, and Simulation of Computer and Telecommunication systems (MASCOTS)

作者： Cui, Jianfeng Lu, Kai Liu, Sheng Natl Univ Def Technol Sch Comp Changsha 410073 Hunan Peoples R China Natl Univ Def Technol Sci & Technol Parallel & Distributed Proc Lab Changsha 410073 Hunan Peoples R China

ISBN: (纸本)9781665458382

In this paper, we conducted a group of evaluations on the SpMV kernel with sequential implementation to investigate cache performance on single-core platforms. We verified a similar pattern inside a suite of sparse matrices covering various domains, which makes cache hit rate extraordinary inspiring in a sequential environment. This implicit regularity drove us to propose a cache space splitting approach, aiming at a better locality in dense vector accessing and utilization of large cache capacity in modern processors. Finally, we explored the design space of cache on Matrix 3000 GPDSP and proposed a group of cache parameters, based on our experimental results.

关键词： SpMV cache sparse matrix PIN simulation

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A Blockchain-Assisted Federated Learning Method for Recommendation systems

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

引用

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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FLMP: Optimizing Training Efficiency of Federated Learning Using Model Pruning with Layer Selection

FLMP: Optimizing Training Efficiency of Federated Learning U...

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

作者： Yuhang Zhou Yangguang Cui Wenfen Shen Weiting Hu School of Computer Engineering and Science Shanghai University Shanghai China School of Computer and Information Technology Shanghai Polytechnic University Shanghai China

ISBN: (数字)9798350352719

ISBN: (纸本)9798350352726

Federated Learning (FL) has emerged as a privacy-preserving method for distributed clients to collaboratively train a model without exposing their raw data. However, the limited communication bandwidth and insufficient computing capacity of clients hinder the efficient deployment of FL applications. Besides, the diverse data distribution among clients may also degrade model performance. To address the aforementioned issues, we propose a novel framework called FLMP. Specifically, our FLMP dynamically identifies and eliminates redundant components within models by analyzing representation similarity and filter importance based on clients' data. This process produces multiple optimal sub-models that are tailored to client capacities. Comprehensive experiments demonstrate that, Compared with other baselines, our proposed framework achieves better performance in both i.i.d and challenging non-i.i.d data scenarios. It achieves up to a 12.31% improvement in model accuracy while maintaining similar communication and computation costs.

关键词： Training Information science Accuracy Federated learning Computational modeling Termination of employment distributed databases

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NFVDC: A flexible and efficient NFV platform for dynamic service chaining

NFVDC: A flexible and efficient NFV platform for dynamic ser...

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international symposium on parallel and distributed Processing with Applications, ISPA

作者： Qiuwen Lu Qingyun Liu Binxing Fang Institute of Information Engineering Chinese Academy of Sciences Beijing China National Engineering Research Center of Information Security Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China Harbin Institute of Technology Shenzhen China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

This paper presents the design and implementation of a novel Network Function Virtualization (NFV) platform, NFVDC, specifically for dynamic service chaining. Unlike traditional service chaining methods, NFVDC supports real-time, reconfigurable service chains that accommodate service functions dynamically joining or leaving the chain. By integrating an advanced traffic steering method, optimized CPU scheduling, and a causal message-passing mechanism, NFVDC addresses challenges in deploying dynamic service chaining, such as traffic steering, resource scheduling, and session state management. Our evaluation demonstrates that NFVDC’s forwarding performance nearly doubles compared to existing solutions when extending service chain lengths to six.

关键词： distributed processing Scalability Refining Dynamic scheduling Robustness Real-time systems Network function virtualization

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Fast Abort-Freedom for Deterministic Transactions

Fast Abort-Freedom for Deterministic Transactions

引用

international symposium on parallel and distributed Processing (IPDPS)

作者： Chen Chen Xingbo Wu Wenshao Zhong Jakob Eriksson University of Illinois at Chicago Microsoft Research

ISBN: (数字)9798350387117

ISBN: (纸本)9798350387124

The efficiency of concurrency control protocols plays a crucial role in transaction processing systems. However, when it comes to deterministic transactions (i.e., transactions with known read/write key sets), existing concurrency control protocols are not optimized to make the most of the determinism. They either force transactions to be aborted and retried, which negatively affects system throughput, or use a centralized scheduler to organize transactions in a way that avoids aborts, but with limited system *** this paper, we present DecentSched, a highly efficient decentralized concurrency control protocol for deterministic transactions. DecentSched employs fine-grained queuing and a decentralized scheduling algorithm to enable serializable concurrent transaction execution with a high degree of parallelism. Extensive evaluation results show that DecentSched can outperform state-of-the-art concurrency control protocols in representative benchmarks.

关键词： distributed processing Protocols Scheduling algorithms Force Process control Tail Benchmark testing

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CGRA-ME 2.0: A Research Framework for Next-Generation CGRA Architectures and CAD

CGRA-ME 2.0: A Research Framework for Next-Generation CGRA A...

引用

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

作者： Omar Ragheb Stephen Wicklund Matthew Walker Rami Beidas Adham Ragab Tianyi Yu Jason Anderson Dept. of Electrical and Computer Engineering University of Toronto Toronto Ontario Canada

ISBN: (数字)9798350364606

ISBN: (纸本)9798350364613

Coarse-grained reconfigurable arrays (CGRAs) belong to the family of configurable processing architectures that have recently attracted increasing interest for their adaptability and efficiency. Research on CGRA architectures and their associated CAD tools is typically conducted empirically, by modelling a CGRA fabric, mapping applications onto it, and then assessing performance, power, and/or area (PPA). In this paper, we describe an open-source framework for such CGRA research - CGRA-ME - CGRA modelling and exploration. We describe the recently released version 2.0 of CGRA - ME, which incorporates a new mapping approach, support for elastic CGRAs, floating point, predication, hybrid RISC-V+CGRA systems, and more.

关键词： Solid modeling Adaptation models distributed processing Conferences Adaptive arrays Fabrics Next generation networking

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Adaptive Neighbor Guided View Reconstruction for Incomplete Multiview Clustering

Adaptive Neighbor Guided View Reconstruction for Incomplete ...

引用

international symposium on parallel and distributed Processing with Applications, ISPA

作者： Siyuan Chen Zhuojie Huang Shuping Zhao Qintai Hu School of Computer Science and Technology Guangdong University of Technology Guangzhou China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

Graph-based multi-view clustering methods have gained significant attention due to their outstanding ability of clustering-structure representation. Considering the influence on the quality of pre-constructed graphs by noise, in this paper, we propose a novel method called ANGVR. Unlike existing methods that aim to directly learn a consensus graph from multi-view data, ANGVR rebuilds the graph constructed from raw data to seek a consensus graph across views for clustering. Furthermore, to guide the construction of graph, an embedding constraint based on neighboring group structures is introduced, which explores the neighborhood structure information corresponding to neighborhood sets. The experimental results show improvements in accuracy of 5.56%, 6.77% and 4.02%, respectively on 3Sources dataset with 10%, 30% and 50% missing view compared to the existing works.

关键词： Learning systems distributed processing Accuracy Clustering methods Noise

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A Hybrid Power Sharing Strategy For parallel Inverters With Interconnect Lines Fault Ride-through

A Hybrid Power Sharing Strategy For Parallel Inverters With ...

引用

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

作者： Kai Yu Li Peng Bowei Lin Key Laboratory of Power Electronics and Energy Management for Ministry of Education of China School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan P. R. China

Conventional power sharing strategies for parallel inverters are mainly divided into two categories. One is based on interconnect lines (ILs) for power information exchange, where the whole system would be subjected to paralysis once a fault hits ILs. Another approach is droop control, where no communication mechanism is required but has uneven power sharing due to the mismatched output impedance. To address this issue, a hybrid power sharing strategy based on adaptive virtual impedance is proposed for low-voltage parallel inverters, which reduces the number of ILs and achieves power sharing evenly. Besides, since the mismatch in output impedance among inverters is compensated by virtual impedance, the system can maintain normal operation even if the ILs fail, which shows superior fault ride-through capability. Simulation results verify the effectiveness of the proposed strategy.

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