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BLP: Block-Level Pipelining for GPUs 21

BLP: Block-Level Pipelining for GPUs

引用

21st ACM International conference on Computing Frontiers (CF)

作者： Feng, Wu-chun Cui, Xuewen Scogland, Thomas de Supinski, Bronis Virginia Tech Blacksburg VA 24061 USA Lawrence Livermore Natl Lab Livermore CA 94550 USA

ISBN: (纸本)9798400705977

Programming models like OpenMP offer expressive interfaces to program graphics processing units (GPUs) via directive-based offload. By default, these models copy data to or from the device without overlapping computation, thus impacting performance. Rather than leave the onerous task of manually pipelining and tuning data communication and computation to the end user, we propose an OpenMP extension that supports block-level pipelining and, in turn, present our block-level pipelining (BLP) approach that overlaps data communication and computation in a single kernel. BLP uses persistent thread blocks with cooperative thread groups to process sub-tasks on different streaming multiprocessors and uses GPU flag arrays to enforce task dependencies without CPU involvement. To demonstrate the efficacy of BLP, we evaluate its performance using multiple benchmarks on NVIDIA V100 GPUs. Our experimental results show that BLP achieves 95% to 114% of the performance of hand-tuned kernel-level pipelining. In addition, using BLP with buffer mapping can reduce memory usage to support GPU memory oversubscription. We also show that BLP can reduce memory usage by 75% to 86% for data sets that exceed GPU memory while providing significantly better performance than CUDA Unified Memory (UM) with prefetching optimizations.

关键词： data transfer GPU optimization pipelining runtime system

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AI-empowered Pose Reconstruction for Real-time Synthesis of Remote Metaverse Avatars 21

AI-empowered Pose Reconstruction for Real-time Synthesis of ...

引用

21st International Joint conference on Computer Science and Software Engineering (JCSSE)

作者： Gu, Xingci Yuan, Ye Yang, Jianjun Li, Longjiang Univ Elect Sci & Technol China Glasgow Coll Chengdu Peoples R China Univ Elect Sci & Technol China SICE Chengdu Peoples R China

ISBN: (纸本)9798350381771;9798350381764

The Metaverse, a synergistic blend of physical and virtual realities, is rapidly evolving as a hub for digital twins and digital avatars, offering transformative potential in domains ranging from smart manufacturing to kinematic examination. This paper introduces an AI-empowered framework for the synthesis of Metaverse avatars through a monocular camera-based system. Our approach integrates a shared control system and advanced multistage filtering to refine sensor data, substantially enhancing pose precision and avatar realism. Experimental results demonstrate our framework's superiority in reducing data jitter and improving network transmission. By harnessing the power of AI and network optimization, our system ensures a cost-effective and accurate solution that enhances user interactivity and presence within the Metaverse. The implications of this work extend beyond immediate interaction benefits, setting a precedent for future immersive and inclusive Metaverse experiences. Future work will focus on expanding the framework's capacity for larger user interactions and incorporating richer features such as nuanced facial and gesture recognition to deliver fully expressive avatars, thereby elevating the Metaverse experience.

关键词： AI Model Metaverse Avatar Synthesis system Pose Reconstruction Monocular Camera Digital Twins Shared Control

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Fuzzy Control of Gun Barrel Movement: Fuzzy Logic and the Gun Barrel's Precision Dance

Fuzzy Control of Gun Barrel Movement: Fuzzy Logic and the Gu...

引用

21st International conference on Global Research and Education (Inter-Academia)

作者： Ribni, F. Varkonyi-Koczy, A. R. Eotvos Lorand Univ Fac Educ & Psychol Doctoral Sch Educ Kazinczy U 23-27 H-1075 Budapest Hungary J Selye Univ Fac Econ & Informat Inst Software Design & Software Dev Hradna 21 Komarno 94501 Slovakia

The scientific and technical aspects of gun barrel movement for effective attack and defense are of ultimate significance. The precise control of the gun barrel is of strategic importance during targeting, especially in changing environmental conditions. Fuzzy logic control offers a powerful alternative to classical and manual solutions to deal with the complexity and uncertainties of dynamic systems, thus increasing targeting accuracy and precision. This approach provides adaptability and intuitive parameterization while simplifying system design and implementation. On the other hand, in fuzzy control management, accurate modeling and visualization of gun barrel movement is essential to achieve efficient aiming and performance. Many papers and realizations can be found on the (automatic) fuzzy control of cannon barrels. In this paper, the authors also suggest an implementation of a fuzzy-controlled cannon barrel. The novelty of this approach is the application of new defuzzification methods, resulting in an accurate solution for the problem. The article starts with a review of the theory and literature on the control of cannon barrels. It is followed by a comparison of different implementations, including simulation tests on the accuracy, and a discussion of some practical issues.

关键词： fuzzy set theory cannon control optimization Hopfield neural networks

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Spectral modeling and experimental validation of optical domain equalization for filtering mitigation 21

Spectral modeling and experimental validation of optical dom...

引用

21st International conference on Optical Communications and Networks, ICOCN 2023

作者： Du, Yuting Yu, Wenbo Lu, Yuan Shi, Hu Chen, Xiao Feng, Zhenhua Zte Corporation State Key Laboratory of Mobile Network and Mobile Multimedia Technology Wdm System Department Wuhan China Shandong P&t Planning and Designing Institute Co. Ltd Jinan China Zte Corporation Wdm System Design Department Wireline Product R&d Institute Nanjing China

An accurate model for optical domain equalization is proposed and verified with experiments. The modeled spectra fit well with measured curves, and prediction accuracy is better than 0.2 dB if used for filtering penal... 详细信息

ISBN: (纸本)9798350343502

关键词： Equalizers

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Framework for Waste Collection Problem in a Low-Tech Urban Setting in India 21st

Framework for Waste Collection Problem in a Low-Tech Urban S...

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21st ISME International conference on Advances in Mechanical Engineering, ISME 2023

作者： Kala, Kaveri Bolia, Nomesh B. Department of Mechanical Engineering Indian Institute of Technology Delhi Hauz Khas New Delhi110016 India

ISBN: (纸本)9789819736539

This paper presents an operations-research-based improvement framework for a waste collection system in the capital city of India, Delhi. The existing manual system divides the urban region into ‘wards’, each with its depot (or garage) of trucks, and a ‘greedy’ method to assign trucks to collect waste from collection points. Here, we propose a framework that encourages the use of OR-based modelling in a low-tech setting. It is based on two types of interventions: system change and system optimization. In system change, a new routing process is developed using a mixed-integer linear programming (MILP) model to address the waste collection problem, which is formulated as a combinatorial optimization known as the vehicle routing problem (VRP). In system optimization, an appropriate intervention link is identified, and minimal changes are introduced to improve the system. A clustering method is utilized for this intervention to achieve efficiency. We found that the system change and the system optimization models led to a decrease of 0.26% and 0.66%, respectively, over the baseline cost. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Combinatorial optimization

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FairSense: Fairness-Aware Urban Sensing with Submodular Spatio-Temporal Reward Maximization 21

FairSense: Fairness-Aware Urban Sensing with Submodular Spat...

引用

21st IEEE International conference on Mobile Ad-Hoc and Smart systems (MASS)

作者： Dey, Tonmoy Wang, Guang Florida State Univ Dept Comp Sci Tallahassee FL 32306 USA

ISBN: (纸本)9798350363999;9798350364002

Urban challenges like air pollution, traffic congestion, and road quality demand precise and timely detection for effective city monitoring. Traditional stationary sensors, costly with limited coverage, have prompted the emergence of mobile sensing (e.g., vehicular urban sensing), which utilizes ubiquitous mobile devices (e.g., sensors on vehicles) for sensing tasks. While commercial vehicles (e.g., taxis) are favored for urban sensing due to easy data collection, biased spatiotemporal distributions often result in uneven sensing coverage. Despite efforts to maximize task completion and incentivize participation, fairness in coverage distribution remains neglected. To address this issue, we propose a hybrid approach integrating Dedicated Sensing Vehicles (DSVs) and commercial vehicles to optimize coverage while accounting for fairness constraints. Routing these DSVs for fairness-aware spatiotemporal coverage poses unique challenges, including achieving high coverage with limited DSVs, prioritizing underserved areas, and ensuring cost efficiency for financial sustainability. To overcome these challenges, in this paper, we design FairSense, a system, which combines the long-term reward optimization capabilities of deep reinforcement learning (DRL) with submodular maximization. FairSense integrates a submodular reward function with spatio-temporal fairness constraints into a DRL algorithm to prioritize long-term gain and fairness, enabling informed path planning for DSVs, thereby enhancing efficiency and fairness in sensing coverage. We evaluate our FairSense with real-world large-scale vehicle GPS data from two cities (i.e., Shenzhen and Beijing), and extensive experiments show our FairSense can effectively improve sensing coverage efficiency and also improve sensing fairness.

关键词： Urban Sensing Spatio-temporal Fairness Submodular optimization Reinforcement Learning

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ASM modeling for Training system and Handwritten Recognition 21

ASM Modeling for Training System and Handwritten Recognition

引用

21st International conference on Emerging eLearning Technologies and Applications, ICETA 2023

作者： Campanella, Pasquina University of Bari "Aldo Moro" Department of Computer Science via Orabona 4 Bari70126 Italy

ISBN: (纸本)9798350370690

In the area of Pattern Recognition, specifically in the field of Handwriting Recognition, will be presented modeling a system of training and recognition of handwritten characters and figures by means an Abstract state Machine (ASM). The processing operation is to perform the thinning in the singular regions of the track pattern handwritten character after determining the thinning in the regular regions. In fact, it is considered a character of the Latin alphabet, the letter "R"in capital letters, or the digit "4", chosen because they contain all the singularities that are possible to find the other characters or figures, and applies them to a technique structural decomposition intended for training and recognition using Hidden Markov Model (HMM). Of course, the same character written by different authors, or by the same author at different times, produces a different result. So, the training activities are more properly configured with an operation for classifying handwritten characters more or less similar, based on slight differences in slope of the stroke. The strokes are the parts of the track, the character components manuscript. The classification of characters allows obtaining a knowledge base to be used in the recognition phase. © 2023 IEEE.

关键词： Hidden Markov models

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system-on-Chip iot for Smart Poultry Manufacturing 21

System-on-Chip iot for Smart Poultry Manufacturing

引用

21st International system-on-Chip Design conference, ISOCC 2024

作者： Leong, Wai Yie Leong, Yuan Zhi Leong, Wai San INTI International University Persiaran Perdana BBN Putra Nilai Negeri Sembilan Nilai71800 Malaysia Schneider Electric Singapore Kallang Singapore

ISBN: (纸本)9798350377088

This study explores the potential of system-on-Chip (SoC) IoT technology in revolutionizing smart poultry manufacturing processes. It discusses the applications and advancements of SoC IoT solutions in enhancing automation, efficiency, and sustainability while ensuring animal welfare, food safety, and environmental responsibility. By integrating sensors, actuators, data analytics, and remote monitoring capabilities into poultry production systems, SoC IoT enables real-time decision-making, proactive management, and optimization of resource utilization. The study examines key challenges, opportunities, and future directions for SoC IoT in poultry manufacturing. © 2024 IEEE.

关键词： Smart manufacturing

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Demo: Horizon: a Real-time Point Cloud Video streaming system over Wireless Networks 23

Demo: Horizon: a Real-time Point Cloud Video Streaming Syste...

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21st Annual International conference on Mobile systems, Applications and Services, MobiSys 2023

作者： Li, Jie Wang, Huiyu Li, Qiyue Li, Zhixin Liu, Xin Liu, Zhi Hefei University of Technology Hefei China State Grid Anhui Electric Power Company Hefei China University of Electro-Communications Tokyo Japan

ISBN: (纸本)9798400701108

As a popular way of representing holographic video or volumetric video, point cloud video can provide users with a highly immersive viewing experience of 6 degrees of freedom (6DoF) and is expected to become the mainstream video format of the future. However, the real-time transmission of point cloud video faces many challenges due to the huge amount of data and the large search space of the optimization problem with constraints. To this end, we propose Horizon, a novel Dynamic Adaptive streaming over HTTP (DASH) based real-time point cloud video streaming system, which aims to maximize the user's viewing experience by predicting the next several steps through a rolling framework and uses a Deep Reinforcement Learning (DRL) based algorithm to achieve a real-time solution to the rolling optimization problem. We have prototyped this system and demonstrated its performance on a state-of-the-art wireless network. © 2023 Owner/Author(s).

关键词： Reinforcement learning

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19th International conference on Future Networks and Communications, FNC 2024 / 21st International conference on Mobile systems and Pervasive Computing, MobiSPC 2024 / 14th International conference on Sustainable Energy Information Technology, SEIT 2024

19th International Conference on Future Networks and Communi...

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19th International conference on Future Networks and Communications, FNC 2024 / 21st International conference on Mobile systems and Pervasive Computing, MobiSPC 2024 / 14th International conference on Sustainable Energy Information Technology, SEIT 2024

The proceedings contain 80 papers. The topics discussed include: randomized protocols for resilient peer-to-peer networks;evaluating the performance of 5G NR in indoor environments: an experimental study;an approach towards reducing training time of the input doubling method via clustering for middle-sized data analysis;analysis of legislative framework governing biometric data;designing a testbed for privacy-preserving voice-based social networks;classical machine learning and large models for text-based emotion recognition;one hop routing optimization approach using machine learning;toward an enhanced stock market forecasting with machine learning and deep learning models;smart agriculture system based on IoT reference architecture and service choreography;and privacy-preserving crime reporting and rewarding in the presence of active insider and outsider adversaries.

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