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FLEXLOG: A Shared Log for Stateful Serverless computing 23

FLEXLOG: A Shared Log for Stateful Serverless Computing

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32nd international Symposium on High-Performance parallel and distributed computing (HPDC) part of the ACM Federated computing Research conference (FCRC)

作者： Giantsidi, Dimitra Giortamis, Emmanouil Tornow, Nathaniel Dinu, Florin Bhatotia, Pramod Univ Edinburgh Edinburgh Midlothian Scotland Tech Univ Munich Munich Germany Huawei Munich Res Ctr Munich Germany

ISBN: (纸本)9798400701559

Stateful serverless applications need to persist their state and data. The existing approach is to store the data in general purpose storage systems. However, these approaches are not designed to meet the demands of serverless applications in terms of consistency, fault tolerance and performance. We present FlexLog, a storage system, specifically a distributed sharedlog, distinctively designedtomeet the requirements of stateful serverless computing while mitigating the relevant system bottlenecks. FlexLog's data layer leverages the state-of-the-art persistent memory (PM) to offer low latency I/O and improve performance. To match the performance, FlexLog's ordering layer employs a scalable design, namely a tree-structure set of sequencer nodes. Importantly, this design provides serverless applications with the flexibility to implement different consistency guarantees and to seamlessly support multi-tenancy configurations. We implement FlexLog from the ground up on a real hardware testbed and we also prove the correctness of our protocols. In particular, we evaluate FlexLog on a cluster of 6 machines with 800 GB Intel Optane DC PM over a 10 Gbps interconnect. Our evaluation shows that FlexLog scales to millions of operations per second while maintaining minimal latency. Our comparison with the state-of-the-art shared log for serverless, Boki, shows that we achieve 10x better throughput in the storage layer and 2x-4x lower latency in the ordering layer, while also providing flexibility to support different consistency properties and multi-tenancy.

关键词： Serverless computing Shared distributed Log Persistent Memory

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Enhancing Network Security with Blockchain Technology

Enhancing Network Security with Blockchain Technology

引用

2024 international conference on Optimization computing and Wireless Communication, ICOCWC 2024

作者： Inzimam Bishnoi, Amit Kumar Menaka, C. Vivekananda Global University Department of Computer Science & Application Jaipur India Teerthanker Mahaveer University Computing Sciences and Information Technology Uttar Pradesh Moradabad India Department of Computer Science and Information Technology Bangalore India

ISBN: (纸本)9798350383348

The block chain era is hastily traction as a sturdy approach to community security. In its conventional shape, block chain integrated is a distributed, immutable, and cryptographically-secured ledger, composed of virtual built in integrated shared amongst a disbursed community of nodes. This distributed ledger presents a platform for relaxed storage and verification of digital assets, built-inclusive of integrated crypto currencies, at the same time as built-integrated users with transactional privateness. As block chain-integrated technology advances, new applications, and protocols are built-integrated to resolve a variety of building situations related to network security. One such application is the utility of smart contracts to verify that community transactions are built-integrated, secure, and legitimate. By means of leverage building block chain integrated distributed ledger generation, clever contracts are capable of automating the execution of transactions at the same time as concurrently verifying their authenticity. This technique is built-in vital integrated fields of built finance and healthcare, as those built industries should manipulate and display access to treasured statistics and builtings. Moreover, smart contracts can be used to the right of entry to manage and authentication protocols, present built integrated customers with greater comfy get entry to data or sources. Any other use case there is for the deployment of distributed denial-of-carrier (DDoS) assault prevention protocols. DDoS attacks are one of the most luxurious and unfavorable online safety threats, and they use big amounts of bandwidth to crush a built in integrated or network-integrated infrastructure. © 2024 IEEE.

关键词： Bandwidth Contracts Conventional Generation Healthcare Infrastructure

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Automatic Generation of distributed-Memory Mappings for Tensor Computations 23

Automatic Generation of Distributed-Memory Mappings for Tens...

引用

2023 international conference for High Performance computing, Networking, Storage and Analysis, SC 2023

作者： Kong, Martin Abu Yosef, Raneem Rountev, Atanas Sadayappan, P. Ohio State University Columbus United States University of Utah Salt Lake City United States

ISBN: (纸本)9798400701092

While considerable research has been directed at automatic parallelization for shared-memory platforms, little progress has been made in automatic parallelization schemes for distributed-memory systems. We introduce an innovative approach to automatically produce distributed-memory parallel code for an important subclass of affine tensor computations common to Coupled Cluster (CC) electronic structure methods, neuro-imaging applications, and deep learning *** propose a novel systematic approach to modeling the relations and trade-offs of mapping computations and data onto multidimensional grids of homogeneous nodes. Our formulation explores the space of computation and data distributions across processor grids. Tensor programs are modeled as a non-linear symbolic formulation accounting for the volume of data communication and per-node capacity constraints induced under specific mappings. Solutions are found, iteratively, using the Z3 SMT solver, and used to automatically generate efficient MPI code. Our evaluation demonstrates the effectiveness of our approach over distributed-Memory Pluto and the Cyclops Tensor Framework. © 2023 Owner/Author(s).

关键词： Tensors

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High-Performance computing for Efficient Transaction Processing: A Comparative Study of parallel and Sequential Execution using SQLite 5

High-Performance Computing for Efficient Transaction Process...

引用

5th international conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2024

作者： Balaji, C.V.Roshan Shaman, K.R. Pritham Raj, V. Kumar, N.Nithish Kumaran, K. School of Computer Science and Engineering Vellore Institute of Technology Chennai campus India

ISBN: (纸本)9798331518097

High-performance computing (HPC) has become an essential tool for improving the efficiency and scalability of transaction processing systems, especially as data volumes continue to grow in fields like finance, e-commerce, and blockchain. This paper presents a comparative study of parallel and sequential transaction processing methods using an SQLite database. Specifically, the research investigates the impact of HPC techniques on transaction throughput, processing speed, and efficiency by simulating 1,000 user transactions. The study employs Python's multiprocessing module to simulate parallel execution, contrasting it with traditional sequential execution. Key performance indicators, including execution time, transaction success rate, and system efficiency, were analyzed to determine the advantages of parallel processing in a transaction-heavy environment. Our results reveal that parallel execution significantly reduces processing time, boosts throughput, and increases overall system efficiency compared to sequential processing. Additionally, the study discusses how parallel processing techniques can address common bottlenecks in transaction-heavy applications and provide solutions for improving the performance of large-scale, data-intensive systems. The findings demonstrate the potential for using HPC to optimize database operations, particularly in systems where high-volume transaction processing is a critical requirement. Future work will explore advanced parallelization strategies, fault tolerance mechanisms, and integrations with distributed databases and blockchain systems. This research contributes to the growing body of knowledge on optimizing transaction processing in high-performance computing environments, with potential applications across various sectors, including financial services, e-commerce, and blockchain technology. © 2024 IEEE.

关键词： Blockchain

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Improving the MPI Remote Memory Access Model for distributed-memory Systems by Implementing One-sided Broadcast 27

Improving the MPI Remote Memory Access Model for Distributed...

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27th international conference on Soft computing and Measurements, SCM 2024

作者： Abuelsoud, Mohamed Paznikov, Aleksej A. Saint Petersburg Electrotechnical University 'LETI' Department of Computer Science and Engineering Saint Petersburg Russia

ISBN: (纸本)9798350363708

Currently, processing large volumes of expanding data efficiently and consistently is a significant challenge. Traditional distributed-memory high-performance computers (HPC) based on message-passing model struggle with inherent synchronization difficulties, limiting their ability to keep pace. Remote Memory Access (RMA, also known as one-sided MPI communications) allows a process to directly read from or write to the memory of another process, bypassing the need for message exchange. Unfortunately, there is no collective operation interface in the current MPI RMA standard. However, RMA has the potential to reduce synchronization costs by enabling concurrent access to shared data structures, distributed among MPI processes' memories. Existing onesided MPI standards offer a linear interface only that hampers parallelization and far from efficient. To bridge this gap, we propose an algorithm design for efficient collective (parallelizable) operations in the RMA paradigm. Our study primarily examines the benefits of collective operations using the broadcast algorithm as an example. Our implementations surpass traditional methods, demonstrating the promising potential of this technique, as more performance tests indicate. © 2024 IEEE.

关键词： parallel programming

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Fault-Tolerant Architectures for distributed Big Data Analytics 1

Fault-Tolerant Architectures for Distributed Big Data Analyt...

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1st international conference on advances in Computer Science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Sudhakaran, Sunil Shah, Samarth Mishra, Manas Kumar Natarajan, Vignesh Bhatt, Jay Goel, Om Mahatma Gandhi University Kerala Kottayam India University at Albany AlbanyNY12222 United States G.L. Bajaj Institute of Technology and Management Department of Computer Science and Engineering Greater Noida201306 India Arizona State University AZ United States Northeastem University BostonMA United States ABES Engineering College U.P. Ghaziabad India

ISBN: (纸本)9798331518578

It has created challenges in the processing of data and analysis, which need to go beyond the traditional centralized architecture to solve the current data volume, speed, and types. To address these challenges, fault-tolerant architectures have become one of the keys to meeting the needs of distributed big data analytics. Failure is a normal part of systems;these architectures are meant to accommodate failures of individual components so that the entire system does not need to stop working or, worse, give false results. They make use of several nodes to operate and retain data in a distributed fashion, which supplies excessive scalability and fault tolerance. This means that even if some nodes fail, a fault-tolerant architecture can still provide redundancy by replicating data across many nodes, giving the system redundancy. Fault-tolerant architectures also utilize efficient data processing techniques like partitioning and data parallel processing, to achieve high performance. This allows real-time and near-real-time analysis of streaming data. © 2025 IEEE.

关键词： Data Analytics

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A Circuit System for High-Speed Multichannel parallel Sampling of Quasi-Optical Signals 3

A Circuit System for High-Speed Multichannel Parallel Sampli...

引用

3rd IEEE international conference on distributed computing and Electrical Circuits and Electronics, ICDCECE 2024

作者： Wang, Zheng Gong, Yongwen Li, Chong Ma, Huijuan Wu, Wencui Guo, Juchuan Guo, Rui Beijing Smart-Chip Microelectronics Technology Co. Ltd. Beijing China State Grid Hebei Markting Service Center Shijiazhuang China Institute Of Microelectronics Chinese Academy Of Sciences Beijing China

ISBN: (纸本)9798350318609

In the advanced alignment measurement and control system of extreme ultraviolet lithography (EUV) equipment, it is necessary to process the optical signal carrying the position information and extract the high-precision marked position *** order to better collect the modulated optical signal, a high-speed multi-channel parallel sampling circuit system is designed, which can collect the light intensity signal in real time, high speed and effectively. Through the corresponding synchronous control system, it can realize the accurate measurement and high precision synchronous control of the advanced measurement and control system. In this circuit system, FPGA chip is used as the main control chip, and the 16-channel scanning modulated optical signal is independently and parallel processed. The sampling frequency is up to *** the basis of VPX bus architecture, the high-speed data transmission interface RapidIO is used for data transmission. The experimental results show that this circuit system can accurately collect the corresponding optical signal in real time and transmit the signal to the upper computer through the signal processing board, and then analyze the optical signal in real time. © 2024 IEEE.

关键词： Field programmable gate arrays (FPGA)

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Flink Task Scheduling Based on LBGA 4

Flink Task Scheduling Based on LBGA

引用

4th international conference on Information Science, parallel and distributed Systems, ISPDS 2023

作者： Cao, Qingzhuo She, Ping Chai, Xiaoli East China Institute of Computing Technology Shanghai China

ISBN: (纸本)9798350337181

In order to solve the problem of uneven task load of different nodes affecting task execution time and throughput caused by the Flink's default scheduling strategy, a task scheduling strategy based on load balancing genetic algorithm (LBGA) in the Flink streaming computing environment is proposed. The strategy starts by calculating resource node performance metrics based on the resource data monitored by the Ganglia module. Considering the matching relationship between task resource requirements and performance metrics, this paper proposes an idea of applying the genetic algorithm (GA) to a streaming computing platform for optimisation. In addition, the LBGA scheduling is proposed on this basis and then experiments are conducted to verify the effectiveness of the algorithm. The experimental results show that compared to the default scheduling algorithm of Flink, the proposed algorithm reduces the execution time of WordCount benchmark tasks by 7.6% and 7.7% for parallelism degrees of 8 and 16 respectively. Not only is the performance of resource node load balancing optimised, but throughput is also significantly improved. © 2023 IEEE.

关键词： Genetic algorithms

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DOA Estimation in A distributed Optimization Framework: A Sparse Approach Based on Consensus ADMM Implementation

DOA Estimation in A Distributed Optimization Framework: A Sp...

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2023 international conference on Images, Signals, and computing, ICISC 2023

作者： Jia, Xiaoyuan Wu, Xiaohuan Zhu, Wei-Ping School of Telecommunication and Information Engineering Nanjing University of Posts and Telecommunications Nanjing China Department of Electrical and Computer Engineering Concordia University Montreal Canada

ISBN: (数字)9781510668171

ISBN: (纸本)9781510668164

Traditional direction-of-arrival (DOA) estimation methods use a single processor to deal with the array data. In recent years, the increasing of the scale of sensor arrays brings heavy workload for single processor. distributed optimization based on multiple local processors has become one of the current research hotspots due to the advantage of parallel computing. In this paper, we proposed a distributed DOA estimation method for massive large-scale arrays. First of all, we provide the signal model and the distributed optimization problem based on sparse representation in a distributed framework. Then, the optimization problem is solved by the alternating direction multiplier method (ADMM), where the overall structure of array is not changed. Compared with the centralized method, our distributed method can greatly reduce the computational complexity while ensuring the estimation accuracy under the large aperture array. Simulation results are provided to show the superiorities of our method. © 2023 SPIE.

关键词： Optimization

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ISAR Imaging of Targets with Complex Motions Based on the Non-uniformed Sampled Integrated Modified Chirp Rate-Quadratic Chirp Rate Distribution 26

ISAR Imaging of Targets with Complex Motions Based on the No...

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26th ACIS international Winter conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed computing, SNPD-Winter 2023

作者： Sun, Zongyang Bai, Linting Xu, Kangfa Xi'an Aeronautics Computing Technique Research Institute Avic Aviation Key Laboratory of Science and Technology on Airborne and Missle-borne Computer Xi'an China

ISBN: (纸本)9798350345865

This paper proposes a new ISAR algorithm for obtaining well-focused images of targets with complex motions in low signal-to-noise ratio (SNR) environments. The algorithm models the echo signals of targets with complex motions as cubic phase signals (CPS) after motion compensations and uses the Non-uniformed Sampled Integrated Modified Chirp Rate-Quadratic Chirp Rate Distribution (NIM-CRQCRD) to estimate CPS parameters. The proposed algorithm compensates the echo signals using the parameter estimates and generates ISAR images of targets with complex motions. Simulation results show that the proposed algorithm has superior anti-noise performance. © 2023 IEEE.

关键词： Parameter estimation

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