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Optimal Allocation of Real Time Measurement in Distribution network Considering network Observability 5

Optimal Allocation of Real Time Measurement in Distribution ...

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5th International conference on Energy, Electrical and Power Engineering, CEEPE 2022

作者： Wu, Zhensheng Fan, Deling Li, Kemeng Zhang, Zhongli Beijing Jiaotong University School of Electrical Engineering Beijing China State Grid Henan Maintenance Company Zhengzhou China

ISBN: (纸本)9781665479059

Power Internet of things measurement terminal device is a new type of information distribution network equipment. If all nodes in the distribution system are equipped with measuring devices, the state estimation problem will be greatly simplified, but this configuration method is difficult to achieve due to economic constraints, so it is necessary to study the optimal distribution scheme of measuring devices. This paper presents an optimized distribution scheme for new distribution measurement terminals, establishes the mathematical model of terminal distribution based on 0-1 integer programming, and formulates the principle and process of node configuration based on tree graph search technology. Based on the measurement characteristics of the Internet of things measurement terminal device applied to power distribution, the calculation methods to make the zero injection nodes and connected nodes observable in the network are deduced, and the terminal distribution methods suitable for large and small-scale systems are proposed. In order to meet the requirements of complete observability and economy of power distribution system, the proposed two methods are configured and compared in different common network architectures. © 2022 ieee.

关键词： Integer programming Power measurement Tree graphs Redundancy Power distribution Distribution networks network architecture

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PTP Security Measures and their Impact on Synchronization Accuracy 18

PTP Security Measures and their Impact on Synchronization Ac...

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18th International conference on network and Service Management (CNSM) - Intelligent Management of Disruptive network Technologies and Services

作者： Rezabek, Filip Helm, Max Leonhardt, Tizian Carle, Georg Tech Univ Munich 18 Network Architectures & Serv Munich Germany

ISBN: (纸本)9783903176515

The Precision Time Protocol (PTP) synchronizes clocks in a network with high precision. The protocol finds use in many areas, such as smart manufacturing, intra-vehicular networks, and critical infrastructure. It becomes clear that striving for security is an important goal. If an attacker succeeds in disturbing the network synchronization, the impact can result in a cascading set of failures. Unfortunately, neither the previous two ieee standards for PTP, nor the popular implementation linuxptp, feature or implement sufficient security options. This work focuses on implementing the security extensions for PTP based on the latest PTP standard ieee 1588-2019 to minimize the threat of attacks and their possible impact. We provide a detailed analysis on PTP synchronicity and security. Based on that, we design and implement software-only tooling to quantify the PTP performance using commercial off-the-shelf hardware and open-source solutions on a linear topology with four to nine hops. The measurements compare the End-to-End (E2E) and Peerto-Peer (P2P) delay calculation modes and the usage of Transparent Clocks (TC) in parts of the network. Both E2E and P2P show visible degradation of clock synchronization with each hop and standard deviations of 118.6 to 571 ns. The TCs perform better, demonstrating a standard deviation between 90 to 140 ns on four to nine hops. We evaluate different logSyncInterval values corresponding to different PTP profiles and do not observe a major impact on the clock behavior caused by the extensions. The measurement precision of the system is within +/- 40 ns. Our evaluation of the newly implemented security extensions to linuxptp shows that the security extensions do not have a significant impact on the clock synchronization and our approach is a feasible addition to PTP. Besides, our contributions can aid network managers in assessing their PTP synchronicity systematically.

关键词： PTP security clocks synchronicity TSN

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P4 Transformer: Towards Unified programming for the Data Plane of Software Defined network 45

P4 Transformer: Towards Unified Programming for the Data Pla...

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45th Annual International ieee-Computer-Society Computers, Software, and Applications conference (COMPSAC)

作者： Hang, Zijun Wang, Yongjie Huang, Shuguang Natl Univ Def Technol Hefei Peoples R China

ISBN: (纸本)9781665424639

P4 (programming Protocol-independent Packet Processors) language provides target-independent programming regardless of the SDN data plane's underlying architecture. However, manufacturers have adapted P4 for their architectures, imposing more restrictions for the standard P4. Consequently, the intention of building a target-independent data plane has been diluted. Accordingly, this paper summarizes three categories of restrictions (branch, state, and primitive) and their differences in the standard P4 and programmable switch. We devised the P4 Transformer to remove the barrier to running standard P4 on a commodity switch, making a step towards unified high-level programming for the SDN data plane. Besides, the P4 Transformer enables originally invalid programs on the switch, thus making the switch more powerful.

关键词： Software Defined network Emerging languages and compilers network applications

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EdgeNN: Efficient Neural network Inference for CPU-GPU Integrated Edge Devices 39

EdgeNN: Efficient Neural Network Inference for CPU-GPU Integ...

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39th ieee International conference on Data Engineering, ICDE 2023

作者： Zhang, Chenyang Zhang, Feng Chen, Kuangyu Chen, Mingjun He, Bingsheng Du, Xiaoyong School of Information China National University of Singapore School of Computing Singapore

ISBN: (纸本)9798350322279

With the development of the architectures and the growth of AIoT application requirements, data processing on edge has become popular. Neural network inference is widely employed for data analytics on edge devices. This paper extensively explores neural network inference on integrated edge devices and proposes EdgeNN, the first neural network inference solution on CPU-GPU integrated edge devices. EdgeNN has three novel characteristics. First, EdgeNN can adaptively utilize the unified physical memory and conduct the zero-copy optimization. Second, EdgeNN involves a novel inference-targeted inter- and intra-kernel CPU-GPU hybrid execution approach, which co-runs the CPU with the GPU to fully utilize the edge device's computing resources. Third, EdgeNN adopts a fine-grained adaptive inference tuning approach, which can divide the complicated inference structure into sub-tasks mapped to the CPU and the GPU. Experiments show that on six popular neural network inference tasks, EdgeNN brings an average of 3.97×, 3.12×, and 8.80× speedups to inference on the CPU of the integrated device, inference on a mobile phone CPU, and inference on an edge CPU device. Additionally, it achieves 22.02% time benefits to the direct execution of the original programs. Specifically, 9.93% comes from better utilization of unified memory, and 10.76% comes from CPU-GPU hybrid execution. Besides, EdgeNN can deliver 29.14× and 5.70× higher energy efficiency than the edge CPU and the discrete GPU, respectively. We have made EdgeNN available at https://***/ChenyangZhang-cs/EdgeNN. © 2023 ieee.

关键词： Graphics processing unit

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Convolutional Neural network for Removal of Environmental Noises from Acoustic Signal

Convolutional Neural Network for Removal of Environmental No...

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2023 International conference on Sustainable Emerging Innovations in Engineering and Technology, ICSEIET 2023

作者： Kar, Shibani Mukherjee, Vishwajeet Sambalpur University Institute of Information Technology Department of Electronics and Communication Engineering Jyoti Vihar Burla Sambalpur India Sambalpur University Institute of Information Technology Department of Basic Sciences and Humanities Jyoti Vihar Odisha Burla India

ISBN: (纸本)9798350329186

Environmental noises affects the quality and intelligibility of acoustic signals. Speech, audio, sound are common examples of acoustic signals. The noises present in our environment especially babble noise can affect the performances of applications such as speech and speaker recognition, hearing aids, mobile telephone etc. The research works presented earlier for the removal of these noises from the recorded signal were based on the estimation of noisy part from the signal to prepare a mask for the removal of the noises. But the recent developments in neural networks has provided a mapping based method that can directly map the noisy speech to clean form. In this paper, a comparative study of convolutional neural network architectures for the enhancement of acoustic signals such as speech is done. The NOIZEUS datasets used for the experimental work is an open source speech dataset. The evaluation metrics PESQ, improvement in SNR, STOI, Segmental SNR (SSNR), and Signal to Distortion Ratio (SDR) are used to compare the performances of these networks for the enhancement of noisy signals. The performance of Convolutional networks in auto-encoder framework performs better in terms of better PESQ, STOI, Segmental SNR, SNR Improvement, SDR for network trained with babble noise at 0dB SNR. © 2023 ieee.

关键词： Deep neural networks

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Efficient Multicore Computing and High-Precision Arithmetic: A Comprehensive Guide to Multicore and Big Number programming

Efficient Multicore Computing and High-Precision Arithmetic:...

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International conference on Communication Systems and network Technologies (CSNT)

作者： Taniya Hasija K. R. Ramkumar Amanpreet Kaur Sudesh Kumar Mittal Bhupendra Singh Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Centre for Artificial Intelligence & Robotics Defence Research and Development Organization Bangalore India

ISBN: (数字)9798350305463

ISBN: (纸本)9798350305470

Today system and application programming is moving toward concurrent and parallel programming with the development of multicore and multiprogramming architectures. In an effort to improve study performance, researchers are looking for more efficient methods to include multiprocessing and multicore programming into their simulation systems. This article provides an overview of multicore programming and illustrates how it can be implemented. The paper also focusing the limitations of primitive data types for diverse applications, especially in the context of computer systems. The article delves into the necessity of big numbers and arithmetic on a significant scale. Focusing on C programming, the article showcases the implementation of big numbers, providing scholars with a comprehensive understanding of the concept and its practical realization.

关键词： Knowledge engineering Codes Multicore processing Parallel programming Communication systems Focusing Computer architecture

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Task-Based Polar Decomposition Using SLATE on Massively Parallel Systems with Hardware Accelerators

Task-Based Polar Decomposition Using SLATE on Massively Para...

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2023 International conference on High Performance Computing, network, Storage, and Analysis, SC Workshops 2023

作者： Sukkari, Dalal Gates, Mark Al Farhan, Mohammed Anzt, Hartwig Dongarra, Jack Innovative Computing Laboratory University of Tennessee KnoxvilleTN United States Kaust Thuwal Saudi Arabia

ISBN: (纸本)9798400707858

We investigate a new task-based implementation of the polar decomposition on massively parallel systems augmented with multiple GPUs using SLATE. We implement the iterative QR Dynamically-Weighted Halley (QDWH) algorithm, whose building blocks mainly consist of compute-bound matrix operations, allowing for high levels of parallelism to be exploited on various hardware architectures, such as NVIDIA, AMD, and Intel GPU-based systems. To achieve both performance and portability, we implement our QDWH-based polar decomposition in the SLATE library, which uses efficient techniques in dense linear algebra, such as 2D block cyclic data distribution and communication-avoiding algorithms, as well as modern parallel programming approaches, such as dynamic scheduling and communication overlapping, and uses openMP tasks to track data dependencies. We report numerical accuracy and performance results. The benchmarking campaign reveals up to an 18-fold performance speedup of the GPU accelerated implementation compared to the existing state-of-the-art implementation for the polar decomposition. © 2023 ACM.

关键词： Parallel programming

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Conditional Wasserstein GAN for Energy Load Forecasting in Large Buildings

Conditional Wasserstein GAN for Energy Load Forecasting in L...

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ieee International conference on Fuzzy Systems (FUZZ-ieee) / ieee World Congress on Computational Intelligence (ieee WCCI) / International Joint conference on Neural networks (IJCNN) / ieee Congress on Evolutionary Computation (ieee CEC)

作者： Nastasescu, George-Silviu Cercel, Dumitru-Clementin Swiss Fed Inst Technol Comp Sci Dept Zurich Switzerland Univ Politehn Bucuresti Comp Sci Dept Bucharest Romania

ISBN: (数字)9781728186719

ISBN: (纸本)9781728186719

Energy forecasting is necessary for planning electricity consumption, and large buildings play a huge role when making these predictions. Because of its importance, numerous methods to predict the buildings' energy load have appeared during the last decades, remaining an open area of research. In recent years, traditional machine learning techniques such as Random Forest, K-Nearest Neighbors, and AutoRegressive Integrated Moving Average (ARIMA) have been replaced with deep learning methods, which have an increased ability to capture underlying consumption trends. However, large amounts of data are mandatory for training neural networks to forecast energy load. With scarce data, augmentation techniques are necessary to ensure high-quality predictions. This paper introduces cWGAN-GP-SN, a conditional (convolutional) Wasserstein Generative Adversarial network with Gradient Penalty and Spectral Normalization used to generate new electrical records. Our architecture leverages the advantages of multiple GAN models to enrich training stability and data quality. The experimental results based on the Building Data Genome dataset show how classification and regression tasks benefit from the enrichment of the dataset. Additionally, adversarial attacks were performed to investigate whether models trained on large amounts of synthetic data are more robust.

关键词： Energy Consumption Generative Adversarial network Wasserstein Distance Data Augmentation Adversarial Attacks

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LEVERAGING AUGMENTED-LAGRANGIAN TECHNIQUES FOR DIFFERENTIATING OVER INFEASIBLE QUADRATIC PROGRAMS IN MACHINE LEARNING 12

LEVERAGING AUGMENTED-LAGRANGIAN TECHNIQUES FOR DIFFERENTIATI...

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12th International conference on Learning Representations, ICLR 2024

作者： Bambade, Antoine Schramm, Fabian Taylor, Adrien Carpentier, Justin Inria Département d'Informatique de l'École Normale Supérieure PSL Research University École des Ponts Marne-la-Vallée France

Optimization layers within neural network architectures have become increasingly popular for their ability to solve a wide range of machine learning tasks and to model domain-specific knowledge. However, designing optimization layers requires careful consideration as the underlying optimization problems might be infeasible during training. Motivated by applications in learning, control and robotics, this work focuses on convex quadratic programming (QP) layers. The specific structure of this type of optimization layer can be efficiently exploited for faster computations while still allowing rich modeling capabilities. We leverage primal-dual augmented Lagrangian techniques for computing derivatives of both feasible and infeasible QP solutions. More precisely, we propose a unified approach that tackles the differentiability of the closest feasible QP solutions in a classical 2 sense. We then harness this approach to enrich the expressive capabilities of existing QP layers. More precisely, we show how differentiating through infeasible QPs during training enables to drive towards feasibility at test time a new range of QP layers. These layers notably demonstrate superior predictive performance in some conventional learning tasks. Additionally, we present alternative formulations that enhance numerical robustness, speed, and accuracy for training such layers. Along with these contributions, we provide an open-source C++ software package called QPLayer for differentiating feasible and infeasible convex QPs and which can be interfaced with modern learning frameworks. © 2024 12th International conference on Learning Representations, ICLR 2024. All rights reserved.

关键词： Quadratic programming

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Parallel and hierarchically-distributed Shoreline Alert Model (SAM) 31

Parallel and hierarchically-distributed Shoreline Alert Mode...

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31st Euromicro International conference on Parallel, Distributed and network-Based Processing, PDP 2023

作者： De Vita, Ciro Giuseppe Mellone, Gennaro Florio, Aniello Charles, Catherine Alessandra Torres Di Luccio, Diana Lapegna, Marco Benassai, Guido Budillon, Giorgio Montella, Raffaele University of Naples 'Parthenope' Dep. of Science and Technologies Naples Italy University of Madrid Carlos Iii Dep. of Computer Science and Engineering Madrid Spain University of Naples 'Federico II' Dept. of Mathematics and Applications Naples Italy

ISBN: (纸本)9798350337631

In this paper, the Shoreline Alert Model (SAM) is presented as a component of a computation platform based on workflows dedicated to extreme weather/marine event simulation. The model aims to mitigate the effects of global change by providing decision-makers, scientists, and engineers with a novel, next-generation tool set for facing extreme weather events and implementing related management or emergency responses. SAM uses a parallelization schema, allowing users to run it on heterogeneous parallel architectures. As a result, SAM produces approximately 24 times faster results than the baseline when using shared memory with distributed memory and dealing with about 20,000 transects along the Campania coastline. The system is based on the algorithms of the open-source numerical models WRF (Weather Research and Forecasting) and WW3 (Wave-watch III) implemented with refraction and shoaling routines together with run-up equations to form the modeling chain used for coastal flooding assessment. © 2023 ieee.

关键词： Parallel architectures

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