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检索条件"任意字段=9th International Conference on Algorithms and Architectures for Parallel Processing"

共 2826 条记录，以下是91-100 订阅

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Experimental Investigation of Fluid Flow Behaviour in parallel Microchannel Using Micro-PIV 9th

Experimental Investigation of Fluid Flow Behaviour in Parall...

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9th international and 49th National conference on Fluid Mechanics and Fluid Power, FMFP 2022

作者： Kumar, Rohit Nashine, Chandan Nadaf, Arman Mohaddin Hussain, Mohd Sakib Pandey, Manmohan Department of Mechanical Engineering IIT Guwahati Guwahati781039 India

ISBN: (纸本)9789819971763

With the miniaturization of the system, the demand for high heat flux removal technologies increases. Innovative technology is the use of microchannel using water as a coolant which can handle the high rate of heat fluxes. For a given pumping power, the rate of flow through the microchannel is low, therefore, many microchannels operating in parallel are required. In this present work, an experimental study of flow through three rectangular parallel microchannels has been carried out. the experiments are performed using micro-PIV at various flow rates and different concentrations of the seeding particles. the post-processing of raw images captured during the micro-PIV experiment is done by PIV Labs software. the experimental analysis is done for various parameters like the concentration of seeding particles and the effect of flow rates. Experimental results are compared with analytical solutions for the parallel microchannel. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Microchannels

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Data Poisoning Attack Against Reinforcement Learning from Human Feedback in Robot Control Tasks 24th

Data Poisoning Attack Against Reinforcement Learning from H...

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24th international conference on algorithms and architectures for parallel processing, ICA3PP 2024

作者： Zhou, Zihui Gao, Yutong Qi, Minfeng Wuhan430074 China Key Laboratory of Ethnic Language Intelligent Analysis and Security Governance Ministry of Education Minzu University of China Beijing100081 China Hainan International College of Minzu University of China Li’an International Education Innovation pilot Zone Hainan572499 China City University of Macau 999078 China

ISBN: (纸本)9789819615247

Reinforcement Learning from Human Feedback (RLHF) technology provides a method for agents to learn human preferences and perform actions that satisfy human desires. this technology was originally used to complete robot control tasks in situations where it was difficult to design a reward function. However, in the process of collecting human feedback, malicious human annotators may launch attacks on RLHF, posing a significant challenge to the technology. Previous research has mostly focused on studying the harm caused by different attacks on RLHF in fine-tuning large language models (LLMs). However, our study is focused on the field of robot control. We designed two data poisoning attacks against human feedback datasets and implemented our attacks in three different offline reinforcement learning (RL) environments. the experimental results show that RLHF is vulnerable to data poisoning attacks in robot control tasks. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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Increased throughput and Power Efficient Multi-Path 1024-Point Radix-22 FFT Processor for Signal processing Applications 7

Increased Throughput and Power Efficient Multi-Path 1024-Poi...

引用

7th international conference on Computing in Engineering and Technology, ICCET 2022

作者： thokala, Mohan Rao Gopi, Telagamalla Department of Electronics and Communication Engineering Siddhartha Institute of Engineering and Technology Telangana State Hyderabad501506 India

ISBN: (纸本)9781839537042

FFT processor used for high-speed signal processing applications, such that to meet the required high-speed applications, FFT processor uses pipeline and parallel processing algorithms to provide such high-speed applications, pipelining techniques such as delay feedback and delay commutation technique are used, for this radix -2k algorithm based FFT processor to provide parallel path signal processing implemented pipeline architectures are used. For high throughput radix-22 radix-23 radix-24 algorithms are used. they reduce both the number of adders and the number of *** processor occupies an area of 3.6mm2 and operating supply voltage of 0.4V-1V, and at a frequency of 600MHz. By taking advantage of Radix-4 algorithm techniques, the processor is implemented with four parallel path signal processing without overhead of hardware compared to the two-path processor. the implemented processor takes less power, approximately 14%, compared to the two-path FFT processor, and the area reduces by 20% using Radix-22 algorithm techniques. Simulation results are observed using Xilinx ISE 14.7 Design Suite using Verilog-HDL coding. © 2022 the Institution of Engineering and Technology.

关键词： Fast Fourier transforms

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Performance, Energy and parallelism: Using Near Data processing in Utility and Cloud Computing 15

Performance, Energy and Parallelism: Using Near Data Process...

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IEEE/ACM 15th international conference on Utility and Cloud Computing (UCC) / 9th international conference on Big Data Computing, Applications and Technologies (BDCAT)

作者： Agha, Gul Mukherjee, Dipayan Sandur, Atul Univ Illinois Dept Comp Sci Urbana IL 61801 USA

ISBN: (纸本)9781665460873

Massive amounts of data are generated by sensor networks, edge computers, IoT devices, and enterprise networks. To process this volume of data requires (1) a scalable programming model that is not only concurrent and distributed, but supports the mobility of data and processes (actors), and (2) algorithms to distribute computations between nodes in a manner that improves overall performance while considering energy use in the system. With appropriate programming tools, we can distribute a given computation in a way that makes effective use of edge devices to improve performance while lowering energy consumption. the paper describes our work building on ideas based on the Actor model of computation. these include characterizing the relation of performance and energy consumption in parallel computation, and methods to support scalable placement mechanisms under dynamically changing network conditions and computational loads on edge devices. the paper will conclude with a presentation with a summary of open research problems.

关键词： edge computing actor model energy efficiency distributed computation

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Research and application of active monitoring technology for power transmission and transformation construction safety in complex environments 9

Research and application of active monitoring technology for...

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9th international conference on Energy System, Electricity, and Power, ESEP 2024

作者： Lin, Zhikan Li, Wenxin Jin, Di Liu, Yuzheng Zhou, Guosheng Chen, Wei Lin, Yujie Lin, Cheng Wu, Jinshan Lin, Junjie Qiu, Peng State Grid Fujian Electric Power Co. Ltd. Construction Branch Fujian Building A No.9 Qinyuan Branch Road Jin'an District Fujian Province Fuzhou City China

ISBN: (纸本)9781510691728

Monitoring systems at power transmission and transformation construction sites often face challenges from complex environments such as haze, low lighting, and strong winds, leading to degraded video quality and stability. To enhance the reliability of these monitoring systems, this study employs three algorithms: image dehazing, low-light enhancement, and wind-induced blur removal. these algorithms are integrated through adaptive weight adjustment and parallel processing. this integration strategy enables the monitoring system to select the optimal algorithm in real-time based on environmental conditions and maintain stable image quality under multiple adverse factors. Experimental results show that the image dehazing algorithm improves PSNR to 28.37 dB in hazy environments, the low-light enhancement algorithm achieves a PSNR of 25.34 dB at night, and the wind-induced blur removal algorithm maintains an SSIM of 0.903 at a wind speed of 4 m/s. Transmission tests in weak signal areas indicate that a compression ratio of 30: 1 to 40: 1 can effectively balance video quality and bandwidth requirements. the monitoring system that integrates multiple algorithms demonstrates good adaptability and robustness in complex environments, providing reliable technical support for safety monitoring at power transmission and transformation construction sites. © 2025 SPIE.

关键词： Haze processing Image dehazing Low-light enhancement Power transmission and transformation engineering Real-time monitoring system Safety monitoring

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Accelerating PDEs with Chiplet-Based processing Chains 9

Accelerating PDEs with Chiplet-Based Processing Chains

引用

9th Annual IEEE international conference on Rebooting Computing, ICRC 2024

作者： Anderson, Jeff El-Ghazawi, Tarek Department of Electrical and Computer Engineering The George Washington University WashingtonDC United States

ISBN: (纸本)9798331541279

Innovative accelerator architectures aim to play a critical role in future performance improvements under ceilings imposed by the end of Moore’s Law. Analog mesh computers are a class of such accelerators, designed to minimize time-to-solution by solving partial differential equations in one shot. However, the limited programmability of analog mesh computers does not support the PDE-solver requirement to match arbitrary PDE mesh shapes. In this work, we introduce a chiplet-based architecture capable of solving arbitrary PDE mesh shapes by chaining neural network acceleration chiplets and analog mesh computers. Specifically, we use physics-informed neural networks to infer the values at the perimeter of the analog mesh computer, and then use the analog mesh computer to solve for the remainder of the PDE. We then investigate resource scheduling strategies for the chiplet-based PDE acceleration architecture. Additionally, we propose a figure of merit that enables comparisons between classes of PDE accelerators. We show that the chiplet-based accelerator shows a speedup of 2x when compared to existing solutions. © 2024 IEEE.

关键词： Mesh generation

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Exploring Quantization Techniques for Large-Scale Language Models: Methods, Challenges and Future Directions 24

Exploring Quantization Techniques for Large-Scale Language M...

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9th international conference on Cyber Security and Information Engineering, ICCSIE 2024

作者： Shen, Ao Lai, Zhiquan Li, Dongsheng National Key Laboratory of Parallel and Distributed Computing National University of Defense Technology China

ISBN: (纸本)9798400718137

Breakthroughs in natural language processing (NLP) by large-scale language models (LLMs) have led to superior performance in multilingual tasks such as translation, summarization, and Q&A. However, the size and complexity of these models raise challenges in terms of computational requirements, memory usage, and energy consumption. Quantization strategies, as a type of model compression technique, have gained attention for their advantages in reducing model size and accelerating inference speed. In this paper, we review the rapid development of quantization techniques for LLMs, and systematically explore methods such as post-training quantization (PTQ), quantization-aware fine-tuning (QAF), and quantization-aware training (QAT), which provide a comprehensive solution to the resource-intensive problem of LLMs from training to post-deployment. We also analyze state-of-the-art benchmarks and datasets to evaluate the effectiveness of quantitative methods in terms of performance retention and computational efficiency. the purpose of this review is to provide researchers with a snapshot of the latest progress in LLM quantization techniques, helping them to quickly grasp the dynamics of the field and understand the key techniques and challenges, so that they can more efficiently devote themselves to this evolving research area. © 2024 Copyright held by the owner/author(s).

关键词： Natural language processing systems

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9th international conference on Smart City Applications, SCA 2024

9th International Conference on Smart City Applications, SCA...

引用

9th international conference on Smart City Applications, SCA 2024

ISBN: (纸本)9783031886522

the proceedings contain 74 papers. the special focus in this conference is on Smart City Applications. the topics include: Tuning Hopfield Neural Networks with Metaheuristic Hy-perparameter Selection;Federated Learning Using Knowledge Distillation for CNN-Based eHealth Data Analysis;a Hybrid Data Mining Model for Early Detection of Lung Cancer Utilizing Supervised Feature Extraction;Whale Optimization Algorithm-Based Feature Selection Combined with the XGBoost Model for Breast Cancer Detection: A Comparative Study;CNN-LSTM Based Network Anomaly Detection in WSN-DS;bibliometric Mapping of Data Catalogs: Exploring Advances and Key Research Actors;Towards an Approach for Extracting UML Class Diagrams Using Advanced Language Models;real-Time Data processing and Big Data Analytics: A Comparative Study of Modern Platforms;Comparative Accuracy Assessment of Orthophotos Produced Using Different UAV and Photogrammetric Software;Horizontal Accuracy Tests on Google Satellite Images Over Naples Added in QGIS;Analyzing AI Models for Turkey Earthquake Disaster Prediction;Predicting Monthly Wheat Crop Coefficients in Morocco Using ANN Models with Limited Meteorological Data: A Study in the Draa-Tafilalet Region;intelligent Climate Control in University Residences for Temporary Guests;Hybrid parallel Architecture Integrating FFN, 1D CNN, and LSTM for Predicting Wildfire Occurrences in Morocco;Identifying NovelSARS-Cov-2 Inhibitors Using a Structure-Based Virtual Screening Approach;Analysis of AI Models for Weather Data Interpretation and Forecasting: Case Study on Temperature Predictions;an Automatic Stop Words Removal in Maghrebi Arabic Dialect Text Classification Using Part of Speech Tagging;business Rules: From Text to Formal Language;comparative Analysis of Large Language Models in Moroccan Darija Translation;machine Learning Approaches for Intrusion Detection in IoT: Literature Review.

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Defense Against Textual Backdoors via Elastic Weighted Consolidation-Based Machine Unlearning 24th

Defense Against Textual Backdoors via Elastic Weighted Cons...

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24th international conference on algorithms and architectures for parallel processing, ICA3PP 2024

作者： Xuan, Haojun Wang, Yajie Wu, Huishu Liu, Tao Zhang, Chuan Zhu, Liehuang Beijing Institute of Technology Beijing China China University of Political Science and Law Beijing China China Academy of Information and Communications Technology Beijing China

ISBN: (纸本)9789819615506

Backdoor attacks pose significant threats to Natural Language processing (NLP) models. Various backdoor defense methods for NLP models primarily function by identifying and subsequently manipulating backdoor triggers within provided samples. However, such methods predominantly operate at the level of data filtering, essentially failing to cleanse the affected model. To solve this problem, we present ELUDE—a groundbreaking method designed to excise the backdoor triggers embedded within the corrupted model. ELUDE’s architecture comprises two core components: the backdoor trigger identifier and the backdoor trigger remover, operating synergistically in a pipeline procedure. While the former employs a perplexity-based approach to locate the backdoor trigger, the latter eradicates the inserted backdoor’s influence on the tainted model using machine unlearning. To counteract the issue of catastrophic forgetting engendered by machine unlearning, we incorporate Elastic Weight Consolidation (EWC) within the backdoor trigger remover. Our experiments on SST-2, OLID, and AG News text classification datasets exemplify the efficacy of ELUDE, as comparative results indicate that ELUDE effectively reduces the success rate of three cutting-edge backdoor attack methods by an average of 60%—simultaneously maintaining comparable performance on the original task. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Natural language processing systems

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the grid portrait analysis method of distribution grid based on multi-attribute grid 9

The grid portrait analysis method of distribution grid based...

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9th international conference on Energy Materials and Electrical Engineering, ICEMEE 2023

作者： Yu, Xiaoyan Lao, Yongchang Hao, Hongzhi Zhou, Zhigang Chen, Chao Economic and Technological Research Institute State Grid Zhejiang Power Co. Ltd. Hangzhou310000 China Zhejiang Dingsheng Engineering Project Management Co. Ltd. China School of Economics and Management North China Electric Power University Beijing102206 China

ISBN: (纸本)9781510672765

As the distribution network system and transportation, energy, municipal, financial, and other service barriers are gradually broken, the comprehensive development of the power network in source network demand, wisdom energy network, and intelligent transportation network as well as the coordinated development of other external systems need to be considered in distribution network planning and operation, aiming to provide new ideas for developing key technologies of new distribution systems. Starting from the distribution network management mechanism of power grid enterprises, this paper constructs a portrait analysis technology for power grid equipment to support the status assessment of the distribution network. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Power grids Power supplies Medium wave Network architectures Correlation coefficients Transformers Cobalt Data processing Statistical modeling Transportation

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