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检索条件"任意字段=Proceedings of the 5th IEEE Symposium on Parallel and Distributed Processing"

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In-Depth Evaluation of a Lower-Level Direct-Verbs API on InfiniBand-based Clusters: Early Experiences

In-Depth Evaluation of a Lower-Level Direct-Verbs API on Inf...

引用

37th ieee International parallel and distributed processing symposium (IPDPS)

作者： Michalowicz, Benjamin Suresh, Kaushik Kandadi Ramesh, Bharath Shafi, Aamir Subramoni, Hari Abduljabbar, Mustafa Panda, Dhabaleswar Ohio State Univ Dept Comp Sci & Engn Columbus OH 43210 USA

ISBN: (纸本)9798350311990

Many High-Performance Computing (HPC) clusters around the world use some variation of InfiniBand interconnects, all of which are powered by the "Verbs" API. Verbs supply a quick, efficient, and developer-friendly method of passing data buffers between nodes through their interconnect(s). In more recent years, the MLX5-DV (Direct Verbs) API has made itself known as a method of providing mechanisms to access and expose low-level structures and buffers to a developer. In principle, MLX5-DV is meant to give improved performance over Verbs thanks to the removal of intermediate layers of software abstraction. In this paper, we examine the inner workings of what this means for potential performance improvement and how MLX5-DV compares to its higher-level counterpart. In addition, we will offer insights on how application developers and MPI programmers can use this to their advantage based on initial experiences with benchmark and application-level results.

关键词： HPC Interconnects InfiniBand RDMA-Core HCA Verbs MLX5DV MLX5

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distributed On-Demand Deployment for Transparent Access to 5G Edge Computing Services

Distributed On-Demand Deployment for Transparent Access to 5...

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37th ieee International parallel and distributed processing symposium (IPDPS)

作者： Hammer, Josef Hellwagner, Hermann Alpen Adria Univ Klagenfurt Inst Informat Technol Klagenfurt Austria

ISBN: (纸本)9798350311990

Multi-access Edge Computing (MEC) is a central piece of 5G telecommunication systems and is essential to satisfy the challenging low-latency demands of future applications. MEC provides a cloud computing platform at the edge of the radio access network. Our previous publications argue that edge computing should be transparent to clients, leveraging Software-Defined Networking (SDN). While we introduced a solution to implement such a transparent approach, one question remained: How to handle user requests to a service that is not yet running in a nearby edge cluster? One advantage of the transparent edge is that one could process the initial request in the cloud. However, this paper argues that on-demand deployment might be fast enough for many services, even for the first request. We present an SDN controller that automatically deploys an application container in a nearby edge cluster if no instance is running yet. In the meantime, the user's request is forwarded to another (nearby) edge cluster or kept waiting to be forwarded immediately to the newly instantiated instance. Our performance evaluations on a real edge/fog testbed show that the waiting time for the initial request - e.g., for an nginx-based service - can be as low as 0.5 seconds - satisfactory for many applications.

关键词： Multi-Access Edge Computing MEC Fog Computing Software-Defined Networking SDN Serverless Computing Container Docker Kubernetes

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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...

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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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2024 5th International Conference on Information Science, parallel and distributed Systems, ISPDS 2024

2024 5th International Conference on Information Science, Pa...

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5th International Conference on Information Science, parallel and distributed Systems, ISPDS 2024

ISBN: (纸本)9798350352719

the proceedings contain 138 papers. the topics discussed include: research on near-infrared spectroscopy calibration transfer algorithm based on piecewise direct standardization and K-Nearest neighbor;research on intelligent data operation and maintenance management scheme;GAIPPTSC: an efficient container tasks orchestration and scheduling algorithm;enhancing network security: machine learning evaluation for intrusion detection in power load management system;UAV anomaly detection model based on integrated multi-modal neural network and neural architecture search;frequency hopping modulation format recognition based on higher-order cyclic cumulants and neural network classifier;cluster-based two-stage client selection strategy for personalized federated learning;and implementation of fir digital filter algorithm in C language on DSP platform.

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Scheduling with Many Shared Resources 37

Scheduling with Many Shared Resources

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37th ieee International parallel and distributed processing symposium (IPDPS)

作者： Deppert, Max A. Jansen, Klaus Maack, Marten Pukrop, Simon Rau, Malin Univ Kiel Dept Comp Sci Kiel Germany Paderborn Univ Paderborn Heinz Nixdorf Inst Paderborn Germany Paderborn Univ Dept Comp Sci Paderborn Germany

ISBN: (纸本)9798350337662

Consider the many shared resources scheduling problem where jobs have to be scheduled on identical parallel machines with the goal of minimizing the makespan. However, each job needs exactly one additional shared resource in order to be executed and hence prevents the execution of jobs that need the same resource while being processed. Previously, an approximation ratio of asymptotically 2 was the best known result for this problem. Furthermore, a 6/5-approximation for the case with only two machines was known as well as a PTAS for the case with a constant number of machines. We present a simple and fast 5/3-approximation and a much more involved but still reasonable 1.5-approximation. Furthermore, we provide a PTAS for the case with only a constant number of machines, which is arguably simpler and faster than the previously known one, as well as a PTAS with resource augmentation for the general case. the approximation schemes make use of the N-fold integer programming machinery, which has found more and more applications in the field of scheduling recently. It is plausible that the latter results can be improved and extended to more general cases. Lastly, we give an inapproximability result for the natural problem extension where each job may need up to a constant number of different resources, namely 3, ruling out better than 5/4 approximations for that case.

关键词： Scheduling Approximation parallel Identical Machines Resource Constraints Conflicts

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Improved DROOP Control Strategy for parallel Operation of Multiple Inverters 5

Improved DROOP Control Strategy for Parallel Operation of Mu...

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5th Asia Energy and Electrical Engineering symposium (AEEES)

作者： Ning, Zhen Yang Chen, Zhe Teng, Yun Hu, Yu Shenyang Univ Technol Shenyang Liaoning Peoples R China Aalborg Univ Depth Energy Technol DK-9220 Aalborg Denmark

ISBN: (纸本)9781665490542

As the connection carrier of distributed power and AC busbar, the inverter can transmit the energy of the distributed power source to the large power grid, so that the inverter can output electricity. To meet the demand for power supply, a corresponding control strategy needs to be adopted. In this paper, the problem of uneven inverter power distribution occurs due to the different impedance of the output line in the microgrid when multiple parallel inverters are running, and the principle of the traditional droop control strategy is briefly analyzed, on this basis, the method is improved, and an improved virtual impedance droop control strategy is proposed. the purpose of this method is to improve the power balance accuracy, which is to reduce the line resistance by adding a virtual impedance to the output line impedance of the inverter. Finally, through simulation verification, the improved virtual impedance droop control strategy can effectively improve the power balance accuracy of the inverter.

关键词： microgrid inverter parallel connection droop control virtual impedance

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Efficient Asynchronous I/O with Request Merging

Efficient Asynchronous I/O with Request Merging

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37th ieee International parallel and distributed processing symposium (IPDPS)

作者： Chowdhury, Md Kamal Hossain Tang, Houjun Bez, Jean Luca Bangalore, Purushotham V. Byna, Suren Univ Alabama Dept Comp Sci Tuscaloosa AL 35487 USA Lawrence Berkeley Natl Lab Sci Data Div Berkeley CA USA Ohio State Univ Dept Comp Sci & Engn Columbus OH 43210 USA

ISBN: (纸本)9798350311990

With the advancement of exascale computing, the amount of scientific data is increasing day by day. Efficient data access is necessary for scientific discoveries. Unfortunately, the I/O performance is not improved, like the CPU and network speed. So, I/O operations take longer time than data generation or analysis. Asynchronous I/O has been proposed to extenuate the I/O bottleneck by overlapping I/O and computation time. However, multiple small write operations can diminish the benefits of asynchronous I/O, as the I/O time becomes significantly longer than the compute time, with little time to overlap with. To overcome these issues, we present an optimization technique to merge small contiguous write operations. We integrated our solution into the HDF5 asynchronous I/O VOL connector and demonstrated the effectiveness of merging HDF5 write operations automatically and transparently without requiring any code change from the application.

关键词： Asynchronous I/O Contiguous Write Merge Merge I/O Merging HDF5 write Write Merge

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Intelligent Test Paper Generation Algorithm Integrating Normal Distribution and parallel Genetic Algorithm 5

Intelligent Test Paper Generation Algorithm Integrating Norm...

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5th International Conference on Intelligent Computing and Human-Computer Interaction, ICHCI 2024

作者： Liu, Chuangye Huang, Guimin School of Computer Science and Information Security Guilin University of Electronic Technology Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin541004 China

ISBN: (纸本)9798350368284

Genetic algorithms have been widely used in intelligent test paper generation systems. However, traditional genetic algorithms cannot ensure that the difficulty of test questions is normally distributed, and are prone to falling into local optimal solutions. To address the above problems, we proposed an intelligent test paper generation algorithm that combines normal distribution and parallel genetic algorithms. In the population initialization stage, we use the cumulative distribution function (CDF) of the normal distribution to initialize the population. In the subsequent genetic operations, we designed a directed mutation mechanism and added KL divergence as a penalty number in the design of the fitness function to ensure that the difficulty of the test questions is normally distributed. At the same time, in order to speed up the efficiency of the algorithm and escape from the local optimal solution, an adaptive migration strategy was introduced. Experimental results show that the difficulty of the test questions generated by this algorithm is normally distributed, and the algorithm performance is better than other algorithms. © 2024 ieee.

关键词： Consensus algorithm

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Asynch-SGBDT: Train Stochastic Gradient Boosting Decision Trees in an Asynchronous parallel Manner 37

Asynch-SGBDT: Train Stochastic Gradient Boosting Decision Tr...

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37th ieee International parallel and distributed processing symposium (IPDPS)

作者： Cheng, Daning Li, Shigang Zhang, Yunquan Tsinghua Univ Dept Comp Sci & Technol Beijing Peoples R China Beijing Univ Posts & Telecommun Sch Comp Sci Beijing Peoples R China Chinese Acad Sci Inst Comp Technol Beijing Peoples R China

ISBN: (纸本)9798350337662

Gradient Boosting Decision Tree (GBDT) is a costly machine learning model. Current parallel GBDT algorithms generally follow a synchronous parallel design: Fork-join parallel manner, like MapReduce. Fork-join parallel manner needs considerable time. thus, we propose whether synchronization is necessary for GBDT training and is asynchronous training manner efficient. In this paper, we solve the above problem by offering an asynchronous algorithm. We try to build a stochastic optimization problem by sampling, which shares the same output with original GBDT training problem and use asynchronous parallel SGD manner to train Gradient step GBDT. We name our algorithm as asynch-SGBDT. Our theoretical and experimental results indicate that compared with the serial GBDT training process, when the datasets' high sample diversity is high and using Gradient step training GBDT, asynch-SGBDT does not slow down convergence speed on the epoch, and the sample diversity of current high-dimensional sparse datasets is usually high. We conduct experiments on a 32-node cluster using four different datasets. the results show that with LightGBM using a single worker as the baseline, LightGBM (the state-of-theart synchronous parallel algorithm implement) on 32 workers achieves 5x-7x speedup, while our asynch-SGBDT on 32 workers increases the speedup to 11x-15x.

关键词： asynchronous parallel GBDT

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Evaluating Asynchronous parallel I/O on HPC Systems 37

Evaluating Asynchronous Parallel I/O on HPC Systems

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37th ieee International parallel and distributed processing symposium (IPDPS)

作者： Ravi, John Byna, Suren Koziol, Quincey Tang, Houjun Becchi, Michela N Carolina State Univ Raleigh NC 27695 USA Lawrence Berkeley Natl Lab Berkeley CA 94720 USA

ISBN: (纸本)9798350337662

parallel I/O is an effective method to optimize data movement between memory and storage for many scientific applications. Poor performance of traditional disk-based file systems has led to the design of I/O libraries which take advantage of faster memory layers, such as on-node memory, present in high-performance computing (HPC) systems. By allowing caching and prefetching of data for applications alternating computation and I/O phases, a faster memory layer also provides opportunities for hiding the latency of I/O phases by overlapping them with computation phases, a technique called asynchronous I/O. Since asynchronous parallel I/O in HPC systems is still in the initial stages of development, there hasn't been a systematic study of the factors affecting its performance. In this paper, we perform a systematic study of various factors affecting the performance and efficacy of asynchronous I/O, we develop a performance model to estimate the aggregate I/O bandwidth achievable by iterative applications using synchronous and asynchronous I/O based on past observations, and we evaluate the performance of the recently developed asynchronous I/O feature of a parallel I/O library (HDF5) using benchmarks and real-world science applications. Our study covers parallel file systems on two large-scale HPC systems: Summit and Cori, the former with a GPFS storage and the latter with a Lustre parallel file system.

关键词： Performance Evaluation Modeling Asynchronous I/O parallel I/O

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