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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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Data-Intensive Computing Modules for Teaching parallel and distributed Computing

Data-Intensive Computing Modules for Teaching Parallel and D...

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

作者： Gowanlock, Michael Gallet, Benoit No Arizona Univ Sch Informat Comp & Cyber Syst Flagstaff AZ 86011 USA

ISBN: (纸本)9781665435772

parallel and distributed computing (PDC) has found a broad audience that exceeds the traditional fields of computer science. This is largely due to the increasing computational demands of many engineering and domain science research objectives. Thus, there is a demonstrated need to train students with and without computer science backgrounds in core PDC concepts. Given the rise of data science and other data-enabled computational fields, we propose several data-intensive pedagogic modules that are used to teach PDC using message-passing programming with the Message Passing Interface (MPI). These modules employ activities that are common in database systems and scientific workflows that are likely to be employed by domain scientists. Our hypothesis is that using application-driven pedagogic materials facilitates student learning by providing the context needed to fully appreciate the goals of the activities. We evaluated the efficacy of using the data-intensive pedagogic modules to teach core PDC concepts using a sample of graduate students enrolled in a high performance computing course at Northern Arizona University. In the sample, only 30% of students have a traditional computer science background. We found that the hands-on application-driven approach was generally successful at helping students learn core PDC concepts.

关键词： Computer Science Education Data-Intensive Computing High Performance Computing parallel and distributed Computing

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Authenticated Selective Disclosure of Credentials in Hybrid-Storage Blockchain

Authenticated Selective Disclosure of Credentials in Hybrid-...

引用

international Conference on parallel and distributed systems (ICPADS)

作者： Ruijiao Tian Lanju Kong Baochen Zhang Xiao Li Qingzhong Li School of Software Shandong University China Dareway Software Co. Ltd China Key Laboratory of Shandong Province for Software Engineering China

The digital representation of credentials has become a necessary way in all aspects of human life, such as healthcare, education, etc. However, the current digital credentials sharing solutions tend to overlook the problem of over-disclosure. The data presentation of credentials is an all-or-nothing process, which results in the leakage of unnecessary data and threatens the privacy of the holder. In this paper, to achieve authenticated selective disclosure of credentials, we first design a hybrid storage model incorporating erasure coding (EC), where the raw data are outsourced to an off-chain distributed storage service provider while only small digest information are stored on-chain to maintain data integrity. Moreover, under the storage model, we propose an authenticated data structure (ADS) which integrates EC and the Merkle B-tree to minimize data sharing. Based on this ADS, a verifiable object (VO) can be generated, which is used to provide proof of the disclosed data without exposing the other data of the credentials. At last, we prove the security of the proposed ADS scheme and the experimental results show that, compared to a baseline solution, the proposed ADS reduces the average building and verification time, without sacrificing much of the transmission cost.

关键词： Privacy Data privacy Costs Education Digital representation Medical services Maintenance engineering

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An Energy Prediction Algorithm for Energy Harvesting Wireless Sensors based on Energy Fluctuation Threshold

An Energy Prediction Algorithm for Energy Harvesting Wireles...

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international symposium on parallel and distributed Processing with Applications, ISPA

作者： Yalin Wang Zhenbo Yuan Yongqi Ge Shuhua Yuan Xin Chen Rui Liu Jintao Gao School of Information Engineering Ningxia University Yinchuan China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

Energy Harvesting Wireless Sensors (EHWS) collect energy with non-linear variations over time, leading to potential energy waste or shortages that degrade their Energy Neutral Operation (ENO) and can cause system outages. To address this, we propose the Double Exponential – Revised Moving Average (DE-RWC) energy prediction algorithm, which dynamically selects between DEMA and RWCMA prediction algorithm during each time slot based on Energy Fluctuation Threshold (EFT). Four experimental scenarios were designed to compare DE-RWC with EWMA, WCMA, and Pro-Energy. The results show that DE-RWC consistently outperforms these models, with improvements of 17.59%, 5.95%, and 15.18% respectively.

关键词： Wireless communication Potential energy Wireless sensor networks Fluctuations Heuristic algorithms Prediction methods Prediction algorithms Sensor systems Sensors Energy harvesting

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parallel Electromagnetic Transient Simulation Method for MMC-based SST Based on Diakoptics

Parallel Electromagnetic Transient Simulation Method for MMC...

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

作者： Yiming Yang Jin Xu Zirun Li Keyou Wang Guojie Li Pan Wu Department of Electrical Engineering Shanghai Jiao Tong University Shanghai China

With the rapid development of renewable energy generation and the distribution network, the dc network has become a hotspot in research and engineering. In the dc network, the power electronic transformer (PET, also known as solid-state transformer, SST) is the crucial interface device. To achieve better characteristics, the SST based on modular-multilevel-converter (MMC) is proposed. The cascade modulization and high switch efficiency of MMC-SST bring challenges to its electromagnetic (EMT) simulation. The numerous submodules increase the order of the node admittance matrix, requiring more computation resources; the high switch frequency requires a smaller time step, decreasing the calculation speed. To deal with these problems, this paper proposes a parallel EMT simulation method based on the diakoptics. This method achieves parallelized calculation at the system level and submodule level by tearing the whole system into subsystems and applying the compact EMTP method. The proposed method is verified in MATLAB and an FPGA-based real-time simulation platform.

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Comparative Investigation among Different Devices Used to Measure Post Arc Current in DC Interruption with Vacuum Interrupters 30

Comparative Investigation among Different Devices Used to Me...

引用

30th international symposium on Discharges and Electrical Insulation in Vacuum, ISDEIV 2023

作者： Tang, Qiang Jia, Shenli Shi, Zongqian Mo, Yongpeng Xi'an Jiaotong University School of Electrical Engineering Xi'an China Sichuan University College of Electrical Engineering Chengdu China

ISBN: (纸本)9784886864369

Four types of devices were used to measure the post arc current of vacuum interrupters after forced current zero for DC interruption. Three of these devices are coils but each uses a different method to integrate di/dt. These are a passive integrator circuit, an active circuit and a digital integrator in a software. A forth device consists of a shunt and pairs of anti-parallel diodes which was introduced to verify the result given by the coils. We found that the current reconstructed by coils' integrators have some inherent problems such as bias and phase shift. Such problems lead to uncertainty of current zero determination and it's hard to tell how large the post arc current's amplitude is. To validate the post arc current measured by coils, the forth device is used because resistive device has advantage of not needing integrator circuit nor digital integration. Strong oscillation due to parasite capacitance of diodes and stray inductance was observed but it actually doesn't affect recognition of post arc current. We compared the results of measured post arc current using these four devices in DC vacuum interruption situations in order to find a reliable post arc current measuring method. Analysis of the coils' working principles proves simple mathematical correction takes effect in giving correct post arc current from the biased original data. © 2023 IEEJ.

关键词： Electric current measurement

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SWEEP: Adaptive Task Scheduling for Exploring Energy Performance Trade-offs

SWEEP: Adaptive Task Scheduling for Exploring Energy Perform...

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international symposium on parallel and distributed Processing (IPDPS)

作者： Jing Chen Madhavan Manivannan Bhavishya Goel Miquel Pericàs Department of Computer Science and Engineering Chalmers University of Technology

ISBN: (数字)9798350387117

ISBN: (纸本)9798350387124

Energy efficiency is becoming a major concern when running parallel computing systems owing to its impact on system reliability and operating cost. Recent works, that focus on energy efficient execution of task-based parallel applications on multi-core systems, leverage a subset of architectural features (core asymmetry, CPU DVFS and memory DVFS) and application attributes (inter-task parallelism, intra-task parallelism and task characteristics) to achieve this goal. More importantly, they have a fixed target metric and do not provide the flexibility to explore energy performance trade-offs (EPTO). We propose SWEEP, a task scheduler that leverages all the aforementioned architectural knobs and application attributes to facilitate EPTO exploration. SWEEP, at a high level, uses a combination of models and heuristics and works by splitting application execution into high parallelism and low parallelism phases. It then uses an adaptive task distribution algorithm, specific to the phase type, that leverages model-based predictions to determine the best task schedule and the DVFS settings for the phase. Moreover, SWEEP is able to flexibly target various EPTO metrics, a feature that is not supported by other proposals. Our evaluation shows that SWEEP achieves 19.9%, 36.4% and 9.5% reduction on average in terms of EDP, ED 2 P and E 2 DP compared to the best performing state-of-the-art.

关键词： Measurement Adaptation models Schedules Multicore processing parallel processing Predictive models Prediction algorithms

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Development and Application Mode Design of Complex Ship Numerical Simulation System Based on SaaS 21

Development and Application Mode Design of Complex Ship Nume...

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21st international symposium on distributed Computing and Applications for Business engineering and Science, DCABES 2022

作者： Zhao, Ji Cheng, Cheng School of IoT Engineering WuXi City College of Vocational Technology Wuxi China China Ship Scientific Research Center Wuxi China

ISBN: (纸本)9781665454629

The current numerical simulation system is developing in the direction of large-scale, complex and service-oriented because of the high integration of numerical simulation technology development and equipment research. However, the numerical simulation research of the three important links of prediction, evaluation and optimization for the ship general performance is highly dependent on foreign commercial software. It is urgent to integrate multidisciplinary fusion methods and data knowledge engineering to implement independent research and development of numerical simulation systems. In order to remodel the research and development mode of ship general performance, the experience and lessons in the development of industrial software are summarized in this paper. The research and development concept of numerical simulation system for ship general performance including 'crowd-innovation and sharing', knowledge collaborative application, and intelligent are proposed to improve ship R & D capability. © 2022 IEEE.

关键词： Ships

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A Fast Scalable Hardware Priority Queue and Optimizations for Multi-Pushes

A Fast Scalable Hardware Priority Queue and Optimizations fo...

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

作者： Samuel Collinson Allan Bai Oliver Sinnen Department of Electrical Computer and Software Engineering Parallel and Reconfigurable Computing Lab University of Auckland New Zealand

ISBN: (数字)9798350364606

ISBN: (纸本)9798350364613

Priority queues (PQ) are an essential data structure for many important algorithms. Hardware implementations of priority queues can accelerate such algorithms significantly. Usually a choice has to be made between very fast (fixed-size) hardware PQs or scalable PQs. Fast hardware queues can provide single cycle push and pop operations, but are limited in size. Scalable hardware queues use embedded memory to achieve scalability, but thereby compromise on speed. This paper proposes a fast and scalable hardware priority queue that can be used for general purpose. It is based on a modular and flexible hybrid design, using a shift register queue combined with a heap-based queue. In the best case, i.e. when only the first queue is needed, push and pop operations only take a single cycle. In an experimental evaluation on a Xilinx FPGA we demonstrate that performance of the hybrid queue maintains a good balance between performance and scalability even for applications where the size of the working set of data can have large variance. We further propose an optimisation of the heap-based queue to support workloads that repeat several consecutive push operations followed by a single pop operation, which is the workload, for instance, in state space search or ray-tracing.

关键词： distributed processing Scalability Sociology Ray tracing Shift registers Data structures Hardware

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Design and Implementation of distributed Video AI Super-Resolution Reconstruction System

Design and Implementation of Distributed Video AI Super-Reso...

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software engineering, Artificial Intelligence, Networking and parallel/distributed Computing (SNPD-Winter), ACIS international Winter Conference on

作者： Jingtao Shang Yangliu Guo Taolong Zhou Wei Li China North Vehicle Research Institute Beijing China Communication University of China School of Computer and Cyber Sciences Beijing China China Industrial Control Systems Cyber EmergencyResponse

This article proposes a distributed video AI super-resolution reconstruction solution based on MapReduce to address the issue of slow video super-resolution reconstruction in a single-machine environment. The solution utilizes scene detection algorithms and precise video segmentation algorithms to divide long videos into multiple video segments based on scenes. These segments are then assigned to different processing nodes for parallel processing, and finally merged to reduce the time required for video AI super-resolution reconstruction. Experimental results demonstrate that this solution effectively improves the speed of video AI super-resolution reconstruction. In addition, this article addresses the issues of low efficiency and low storage space utilization in the distributed storage system HDFS (Hadoop distributed File System) when storing small files, specifically video segments. It proposes an optimized storage solution based on HDFS and Redis. This solution merges small files and constructs a small file merging and storage model on Redis, effectively alleviating the memory pressure on the NameNode in HDFS when storing a massive number of small files. Experimental results demonstrate that this solution sacrifices a certain degree of read/write performance but mitigates the rapid growth of NameNode memory. This solution holds significant theoretical and practical significance.

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MAAD: A distributed Anomaly Detection Architecture for Microservices systems

MAAD: A Distributed Anomaly Detection Architecture for Micro...

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international symposium on parallel and distributed Processing (IPDPS)

作者： Rongyuan Tan Zhuozhao Li Department of Computer Science and Engineering Southern University of Science and Technology China Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology China

ISBN: (数字)9798350387117

ISBN: (纸本)9798350387124

Anomaly detection plays a critical role in microservices systems by enabling system administrators to promptly detect and respond to anomalies. However, existing anomaly detection systems often necessitate the centralization of log and trace data from diverse system components and rely on resource-intensive statistical methods or deep learning models for analysis. This approach impedes real-time anomaly detection and requires a significant demand on computing resources. In this paper, we design a multi-agent-based, distributed anomaly detection architecture called MAAD to address the limitations. MAAD consists of a collection of agents that cooperate together to identify abnormal behaviors in a distributed manner. Each agent is deployed along with a single service and applies lightweight machine learning techniques to perform local anomaly detection based on its own logs, local context, and information extracted from its parent span *** preserve the graph information in a microservices request, an agent can communicate essential features with each other, taking into account the collective patterns learned from the prior services. We evaluate the effectiveness of MAAD on two microservices datasets, TrainTicket and MicroSS, and show that MAAD achieved high precision (up to 95.8%) and recall (up to 99.6%), outperforming state-of-the-art centralized anomaly detection approaches. Compared to centralized approaches, MAAD reduces the amount of transferred data before anomaly detection by approximately 88%, facilitating real-time anomaly detection. Furthermore, the lightweight nature of MAAD allows for rapid anomaly detection with minimal impact on microservices systems. Compared to DeepLog, MAAD saves approximately 92% detection time without using GPU accelerators.

关键词： Deep learning distributed processing Statistical analysis Microservice architectures Graphics processing units Computer architecture Feature extraction

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