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International Symposium on parallel and distributed Processing (IPDPS)

作者： Yi Ju Amir Raoofy Dai Yang Erwin Laure Martin Schulz Max Plank Computing and Data Facility Technical University of Munich NVIDIA GmbH

The mining of multi-dimensional time series is a crucial step in gaining insights into data obtained from physical systems and from monitoring infrastructures. A widely accepted approach for this challenge is the matrix profile, which, however, is computationally very expensive. It relies on calculating large correlation matrices coupled with sort operations across all dimensions of the data, as well as on performing inclusive scans. All of these steps are inherently data parallel and can, therefore, benefit from execution on GPUs, and even more so from horizontal scaling on multiple GPUs. In addition, the nature of the matrix profile calculation allows the exploitation of reduced precision on GPUs. This offers further improvements to enable the analysis of ever growing data sets in real-world scenarios. Based on these motivations, we introduce the first parallel algorithm for multi-dimensional matrix profile on multiple GPUs exploiting reduced precision modes and provide a highly opti-mized implementation using novel optimization techniques. On one NVIDIA A100 GPU, our implementation achieves a 54x performance improvement in comparison to an optimized single-node execution on a state-of-the-art CPU-based implementation relying on double-precision computation and an additional factor of 1.4x when switching to reduced precision while maintaining sufficient accuracy. We study the accuracy and performance trade-offs for our proposed algorithm in detail and present synthetic and real-world case studies to demonstrate how the reduced precision improves the performance, while accomplishing sufficiently accurate results.

关键词： time series analysis Layout Graphics processing units Switches Data mining Synchronization parallel algorithms

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Implementing an Intelligent Irrigation System in Oman Using Machine Learning Technique 3

Implementing an Intelligent Irrigation System in Oman Using ...

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3rd IEEE International Conference on Device Intelligence, Computing and Communication Technologies, DICCT 2025

作者： Stephen, Vimal Kumar Sharma, Sanjiv Al-Jufaili, Zaina Rashid Salim Jayapal, Senthil University of Technology And Applied Sciences College of Computing and Information Sciences Ibra Oman

ISBN: (纸本)9798331543358

In this study, machine-learning technique is used to collect environmental data in real time and measures other aspects like soil moisture, temperature, water level, humidity. Water use efficiency has recently increased because to new agricultural techniques, sophisticated sensors as Micro Controller, and Wireless Sensor Network (WSN). Irrigation Fault Detection method based on XGBoost (IFD-XGBoost) Algorithm used as proposed method as robust to missing values imputing them naturally during tree splitting. The Suggested method is optimized for speed, using parallel and distributed computing to make predictions faster compare to other Regression Algorithm and avoid over fitting. Using Min-Max Normalization, features with different sizes and units can affect the efficacy of several machine learning algorithms. By warping the statistical relationship between features, removal of noisy data and error detection can reduce the machine learning models' efficiency. Lasso Regression is a linear model that combines regularization and feature selection. Additionally, less data will be kept in the centralized cloud as a result. Using the IFD-XGBoost Algorithm's ability to handle missing data, learn from past errors, and adjust parameters, our proposed approach would be the best model to implement. It outperform from other algorithm in Predictive accuracy, making it reliable for calculating water needs and forecasting weather. Investigating the implementation of several machine learning models that can offer the best real-world irrigation decision management is the main goal of this article. The comparative analysis to evaluate the IFD-XGBoost method yielded a minimum RMSE of 0.3524, MAE of 0.1832, MAPE of 4.24 with the highest accuracy of 99.2%, precision of 96.2% and AUC-ROC of 95%, indicates when combined, these metrics provide insightful data about each model's ability to anticipate future developments in irrigation systems. © 2025 IEEE.

关键词： distributed cloud

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Improving the Performance of Deduplication-Based Storage Cache via Content-Driven Cache Management Methods

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IEEE TRANSACTIONS ON parallel AND distributed systems 2021年第1期32卷 214-228页

作者： Tan, Yujuan Xu, Congcong Xie, Jing Yan, Zhichao Jiang, Hong Srisa-an, Witawas Chen, Xianzhang Liu, Duo Chongqing Univ Coll Comp Sci Chongqing 400044 Peoples R China HewlettPackard Enterprise San Jose CA 95002 USA Univ Texas Arlington Comp Sci & Engn Dept Arlington TX 76019 USA Univ Nebraska Lincoln Comp Sci & Engn Lincoln NE 68588 USA

Data deduplication, as a proven technology for effective data reduction in backup and archiving storage systems, is also showing promises in increasing the logical space capacity for storage caches by removing redundant data. However, our in-depth evaluation of the existing deduplication-aware caching algorithms reveals that they only work well when the cached block size is set to 4 KB. Unfortunately, modern storage systems often set the block size to be much larger than 4 KB, and in this scenario, the overall performance of these caching schemes drops below that of the conventional replacement algorithms without any deduplication. There are several reasons for this performance degradation. The first reason is the deduplication overhead, which is the time spent on generating the data fingerprints and their use to identify duplicate data. Such overhead offsets the benefits of deduplication. The second reason is the extremely low cache space utilization caused by read and write alignment. The third reason is that existing algorithms only exploit access locality to identify block replacement. There is a lost opportunity to effectively leverage the content usage patterns such as intensity of content redundancy and sharing in deduplication-based storage caches to further improve performance. We propose CDAC, a Content-driven Deduplication-Aware Cache, to address this problem. CDAC focuses on exploiting the content redundancy in blocks and intensity of content sharing among source addresses in cache management strategies. We have implemented CDAC based on LRU and ARC algorithms, called CDAC-LRU and CDAC-ARC respectively. Our extensive experimental results show that CDAC-LRU and CDAC-ARC outperform the state-of-the-art deduplication-aware caching algorithms, D-LRU, and D-ARC, by up to 23.83X in read cache hit ratio, with an average of 3.23X, and up to 53.3 percent in IOPS, with an average of 49.8 percent, under a real-world mixed workload when the cache size ranges from 20

关键词： Metadata Cache storage Redundancy Performance evaluation distributed databases Degradation Indexes Data deduplication storage cache content sharing

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多参数约束分布式储能逆变并联均衡控制

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中国测试 2024年第10期50卷 35-41,58页

作者：王佳兴李佳静谷志锋乔宇郝东墉霍宇飞石家庄铁道大学电气与电子工程学院河北石家庄050043 江西清华泰豪三波电机有限公司江西南昌330096

为解决分布式储能逆变并联系统功率分配受储能系统实时状态影响的问题,通过建立逆变并联下垂系数与储能系统剩余电量、系统端电压、放电时长、额定容量之间的函数表达,并结合剩余电量无迹卡尔曼滤波估计算法和虚拟电感下垂控制算法,提... 详细信息

为解决分布式储能逆变并联系统功率分配受储能系统实时状态影响的问题,通过建立逆变并联下垂系数与储能系统剩余电量、系统端电压、放电时长、额定容量之间的函数表达,并结合剩余电量无迹卡尔曼滤波估计算法和虚拟电感下垂控制算法,提出一种新的多参数约束分布式储能逆变并联均衡控制策略。在多种工况下样机测试和仿真实验表明,新算法能够提高储能系统功率分配均衡度性,通过对同容量不同SOC初值、不同容量以及突增负载等工况进行分析验证,在突增负载工况下电流控制精度较为明显提升约0.6%,且无畸变。在剩余电量、端电压、额定容量等存在偏差的状况下,并联功率均能够自动完成动态调节,实现SOC的均衡控制。最后通过等比例实物验证,结果实现均衡效果。

关键词：分布式储能无迹卡尔曼滤波储能逆变并联虚拟电感多参数约束

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Two-Level parallel Augmented Schur Complement Interior-Point Algorithms for the Solution of Security Constrained Optimal Power Flow Problems

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IEEE TRANSACTIONS ON POWER systems 2020年第2期35卷 1340-1350页

作者： Kardos, Juraj Kourounis, Drosos Schenk, Olaf Univ Svizzera Italiana Inst Computat Sci Adv Comp Lab CH-6904 Lugano Switzerland NEPLAN AG CH-8700 Kusnacht Switzerland

Modern power grids incorporate renewable energy at an increased pace, placing greater stress on the power grid equipment and shifting their operational conditions towards their limits. As a result, failures of any network component, such as a transmission line or power generator, can be critical to the overall grid operation. The security constrained optimal power flow (SCOPF) aims for the long term precontingency operating state, such that in the event of any contingency, the power grid will remain secure. For a realistic power network, however, with numerous contingencies considered, the overall problem size becomes intractable for single-core optimization tools in short time frames established by real-time industrial operations. We propose a parallel distributed memory structure exploiting framework, BELTISTOS-SC, which accelerates the solution of SCOPF problems over state of the art techniques. The acceleration on single-core execution is achieved by a structure-exploiting interior point method, employing successive Schur complement evaluations to further reduce the size of the systems solved at each iteration while maintaining sparsity, resulting in lower computational resources for the linear system solution. Additionally the parallel, distributed memory implementation of the proposed framework is also presented in detail and validated through several large-scale examples, demonstrating its efficiency for large-scale SCOPF problems.

关键词： Security constraints optimal power flow non-linear programming interior point method parallel algorithms

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Research on distributed parallel computing technology of airborne test data

Research on distributed parallel computing technology of air...

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2020 Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2020

作者： Yan, Lijun Shi, Fenglei Zhu, Hongxiang Xi'an710089 China

ISBN: (纸本)9781728160665

Aiming at the task requirements of a small fast-moving test vehicle with small space, short flight support interval and real-time task evaluation, at the same time, the future flight test is faced with many test parameters, wide distribution of test systems, and high real-time data requirements. To solve the rapid acquisition test evaluation data in a specific environment, we design distributed system, data analysis and fusion technology, embedded parallel computing and other technologies to realize the parallel computing and real-time processing on airborne data. The calculated data results are directly telemetry or recorded for real-time monitoring and rapid assessment of missions. The design meets the requirements of rapid real-time evaluation during the flight test and improves the flight test efficiency. © 2020 IEEE.

关键词： real time systems

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Simulating Heterogeneous Models on Multi-Core Platforms using Julia's Computing Language parallel Potential 24

Simulating Heterogeneous Models on Multi-Core Platforms usin...

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IEEE/ACM 24th International Symposium on distributed Simulation and real time Applications (DS-RT)

作者： Suslov, Sergey Schiek, Michael Robens, Markus Grewing, Christian van Waasen, Stefan Res Ctr Julich ZEA Elect Syst 2 Julich Germany

ISBN: (纸本)9781728173436

This paper addresses the questions of high-level system modelling using heterogeneous multi-tool modelling environment on parallel multi-core processing systems for simulation acceleration. The modelling technique has been applied for high-level validation of a high-precision Indoor Positioning System for Motion Analysis (IPS-MA) developed in the Central Institute Electronic systems (ZEA-2) of the Research Center Juelich GmbH. The heterogeneous modelling environment has been built using an implementation-level model designed in Matlab Simulink, a verification model for describing the system environment using Modelica language, and Julia language for automatic generation of binding modelling environment and parallelizing the simulation of the overall model. The approach showed a good flexibility in system description and verification in the multi-instrument modelling environment and a good performance gain due to simulation parallelism.

关键词： distributed simulation high level system modelling functional verification Julia computing language Modelica parallelized simulation

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Gradient-Based Multi-Area Distribution System State Estimation

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IEEE TRANSACTIONS ON SMART GRID 2020年第6期11卷 5325-5338页

作者： Zhou, Xinyang Liu, Zhiyuan Guo, Yi Zhao, Changhong Huang, Jianqiao Chen, Lijun Natl Renewable Energy Lab Power Syst Engn Dept Golden CO 80401 USA Univ Colorado Dept Comp Sci Boulder CO 80309 USA Univ Texas Richardson Dept Mech Engn Richardson TX 75080 USA Chinese Univ Hong Kong Dept Informat Engn Hong Kong Peoples R China IIT Dept Elect & Comp Engn Chicago IL 60616 USA

The increasing distributed and renewable energy resources and controllable devices in distribution systems make fast distribution system state estimation (DSSE) crucial in system monitoring and control. We consider a large multi-phase distribution system and formulate DSSE as a weighted least squares (WLS) problem. We divide the large distribution system into smaller areas of subtree structure, and by jointly exploring the linearized power flow model and the network topology, we propose a gradient-based multi-area algorithm to exactly and efficiently solve the WLS problem. The proposed algorithm enables distributed and parallel computation of the state estimation problem without compromising any performance. Numerical results on a 4,521-node test feeder show that the designed algorithm features fast convergence and accurate estimation results. Comparison with traditional Gauss-Newton method shows that the proposed method has much better performance in distribution systems with a limited amount of reliable measurement. The real-time implementation of the algorithm tracks time-varying system states with high accuracy.

关键词： State estimation Voltage measurement Reliability Distribution networks Monitoring real-time systems Distribution system state estimation multi-area state estimation distributed algorithm multi-phase system large system simulation

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ODRE workshop: Using SIL Arithmetic to Design Safe and Secure systems 23

ODRE Workshop: Using SIL Arithmetic to Design Safe and Secur...

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IEEE 23rd International Symposium on real-time distributed Computing (ISORC)

作者： Menon, Catherine Iacovelli, Saverio Kirner, Raimund Univ Hertfordshire Dept Comp Sci Hatfield Herts England

ISBN: (纸本)9781728169583

In a safety-critical system each service has a specific level of safety criticality. Safety standards use classifications like Safety Integrity Levels (SIL), to describe the design requirements for the individual services of a system. Techniques like redundancy can be used to achieve a higher overall dependability than the used individual components provide. Using the notion of SIL, this can be called SIL arithmetic. In this paper we describe the concept of SIL arithmetic and point out how different safety standards provide hints for their support of using SIL arithmetic. We highlight the principal benefits of SIL arithmetic and provide simple examples. But the use of SIL arithmetic in a concrete system design can also have its pitfalls, which we also discuss in this paper. We specifically discuss these issues in the context of scheduling techniques for mixed-criticality systems, where resource shortages are to be handled by the scheduler.

关键词： Mixed-criticality scheduling Cybersecurity Safety Integrity Levels (SIL) Industrial Control systems (ICS) Cyber-physical systems

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Utility intertie multi-photovoltaic-inverters-based microgrid control for solar rooftop

IET ENERGY SYSTEMS INTEGRATION

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IET ENERGY systems INTEGRATION 2022年第2期4卷 247-266页

作者： Chauhan, Shubhra Singh, Bhim Indian Inst Technol Delhi Dept Elect Engn New Delhi 110016 India

The solar photovoltaic (PV)-based microgrid is one of the most ideal renewable energy resources. This paper presents a utility grid intertie multi-PV-inverter-based microgrid (MG) control for the solar rooftop application. The main and ancillary voltage source converters (VSCs) DC links are assimilated with PV arrays of independent maximum power point tracking (MPPT) algorithms for the economical and efficacious single-stage configuration. At the point of common coupling (PCC), parallel VSCs arrangement increases the MG's power rating with distinctive local loads. In normal circumstances, the current control methodology is employed by the main VSC under the grid-interactive mode. Conversely, in some grid contingency conditions under the isolated mode, its control transfers to the voltage control, which regulates the frequency and the voltage at PCC and acts like a grid-forming inverter. The ancillary VSC operation is implemented with the current control algorithm. The main VSC supplies the active power towards the grid and accomplishes the load requirement, whereas the ancillary VSC retains its load demand in a grid-interactive mode and also regulates the load requirement in an islanded mode of operation. The utilization of feed-forward components for PV arrays powers in the VSCs current control techniques improves the MG dynamic performance. The seamless mode transfer performance of the main VSC is implemented via a power electronics switch. The MATLAB software is used to model a microgrid and its performance is analysed via RT-LAB in real time through the OPAL-RT (OP4510) controller for various scenarios, that is, varying solar insolation, load alterations and unbalanced non-linear loads. The utilization of the modified Kwong's algorithm-based current control enhances the power quality such as harmonics current elimination and improvement in the power factor. The voltage profile of PCC voltages is enhanced via using a modified Kwong's algorithm-based filter in the

关键词： intertie multiphotovoltaic-inverters-based microgrid control power generation control least-mean-square method PV arrays distributed power generation distinctive local loads grid-interactive mode seamless mode transfer performance nonlinear loads single-stage configuration mean square error methods economical stage configuration OPAL-RT controller VSC current control techniques power electronics Kwong algorithm RT-LAB solar photovoltaic-based microgrid power supply quality invertors feed-forward components harmonics current elimination grid-forming inverter power electronics switch voltage-source convertors maximum power point tracking algorithms active power power quality ideal renewable energy resources voltage source converters IEEE-519 standard voltage controller solar rooftop application PCC voltages power factor voltage control total harmonic distortion grid contingency conditions solar power stations maximum power point trackers photovoltaic power systems electric current control power grids MG power rating MPPT harmonic distortion

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