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Accelerating small matrix multiplications by adaptive batching strategy on GPU 24

Accelerating small matrix multiplications by adaptive batchi...

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24th IEEE international conference on High Performance Computing and Communications, 8th IEEE international conference on Data Science and Systems, 20th IEEE international conference on Smart City and 8th IEEE international conference on Dependability in sensor, Cloud and Big Data Systems and Application, HPCC/DSS/SmartCity/DependSys 2022

作者： Zhang, Yaqing Wang, Yaobin Mo, Zhangbin Zhou, Yong Sun, Tao Xu, Guang Xing, Chaojun Yang, Liang School of Computer Science and Technology Key Laboratory of Testing Technology for Manufacturing Process in Ministry of Education Southwest University of Science and Technology Mianyang China Huawei Technologies Co.Ltd Shenzhen China Loongson Technology Corporation Limited Peking China

ISBN: (纸本)9798350319934

General matrix multiplication (GEMM) is a key operator in a wide range of fields such as machine learning, scientific computing, and signal processing. In practice, the matrix sizes are usually too small to make full use of GPU resources in many applications. To this end, previous work has attempted to batch small GEMMs by designing a CUDA core to process multiple GEMMs simultaneously. It divides the GEMM into multiple tiles, and then process a tile in a thread block. However, the approach only processes one tile per thread block and allocates the number of thread blocks based on the size of the largest matrix in the batch. It will make some thread blocks and threads idle. In this paper, we propose a batching strategy to batch small GEMMs with the consideration of several factors, including tile number, block number, and block size. We process multiple tiles in a thread block. Different tiles may need different block size and block number, we select the optimal scheme adaptively according to the hardware resources occupancy. Our proposed strategy achieves the performance improvement of batched GEMM by improving GPU occupancy. The experimental results show that our batching strategy can achieve about 1.7X speedup on average over the MAGMA and about 1.2X performance improvement on average over the state-of-the-art L-gemm. © 2022 IEEE.

关键词： Graphics processing unit

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Cane Vision: A Cutting-Edge Mobility Assistance System for the Visually Impaired

Cane Vision: A Cutting-Edge Mobility Assistance System for t...

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2024 international conference on Communication, Computing and Energy Efficient technologies, I3CEET 2024

作者： Waghmode, Rushikesh Ramchandra Bhonsle, Sanketvardhan Satyajeet Shetty, Ruchit Ramesh Iyer, Deepti Jayananth Kumar, Sachin Chakrabartty, Shubhro D Y Patil International University School of Computer Science Engineering and Applications Pune India Galgotias College of Engineering and Technology Department of Electronics and Communication Engineering Greater Noida India

ISBN: (纸本)9798331541583

People with visual impairments face difficulties navigating unfamiliar areas, restricting their daily activities. They often require help from others, guide dogs, or expensive electronic aids to move safely. In this paper, an advanced mobility assistance system for the visually impaired people is created to address the challenges. This affordable, lightweight device uses an image processing concept to alert users about obstacles and puddles through vibrations. It also precisely measures the distance to obstacles, with different vibration patterns indicating varying levels of proximity. This functionality is achieved by combining an ultrasonic sensor, vibration motor, and ESP32 CAM module, all controlled by an ESP32 microcontroller. These components, strategically placed on the cane, provide efficient guidance and improved mobility for visually impaired users. © 2024 IEEE.

关键词： Microcontrollers

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IoT-Enabled Smart Home Management System Featuring Fault Detection and Remote Monitoring

IoT-Enabled Smart Home Management System Featuring Fault Det...

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international conference on Computer and Communications technologies (ICCCT)

作者： Devarasetty Charan Teja M Bala Narasimha Rao Gokulakrishnan D SRM Institute of Science and Technology Chennai India

ISBN: (数字)9798331537579

ISBN: (纸本)9798331537586

The fast progression of Internet of Things (IoT) technology has facilitated the creation of sophisticated solutions for home automation and management. This study introduces a full smart home management system that incorporates defect detection and power management capabilities. The system utilises an ATmega 328 microcontroller, interfaced with many sensors and actuators to oversee and regulate electrical load situations. A voltage sensor and variable resistor are used to identify abnormalities, facilitating real-time defect detection. The system interacts with the user via an LCD display and facilitates remote monitoring via an IoT-based website. Moreover, vital notifications are sent to pertinent stakeholders using GSM technology, enabled via UART communication, guaranteeing prompt responses to fault circumstances. This IoT-enabled intelligent solution improves safety, energy efficiency, and automation in residential settings. The suggested system design is scalable and adaptive, making it appropriate for diverse home applications. It enables ongoing surveillance and problem identification, reducing the danger of electrical malfunctions and improving residential security. The system utilises wireless GSM communication to notify users of possible hazards, regardless of their location away from home. Moreover, the incorporation of IoT for remote access facilitates effortless control and instantaneous data visualisation, offering users insights into energy use and system efficacy. This article examines the design, implementation, and testing of the smart home management system, emphasising its practical applicability in contemporary smart houses.

关键词： GSM Microcontrollers Surveillance Smart homes Real-time systems sensor systems Security Intelligent sensors Remote monitoring Testing

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Comprehensive Mix-Method Approach for Efficient Waste Management using IoT-Driven Solutions

Comprehensive Mix-Method Approach for Efficient Waste Manage...

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Emerging Smart Computing and Informatics (ESCI), conference on

作者： Neha Gupta School of Computer Applications Manav Rachna International Institute of Research & Studies Faridabad Haryana

ISBN: (数字)9798331515683

ISBN: (纸本)9798331515690

Escalating the global waste management crisis calls for innovative technological interventions transforming the age-old practice of traditional waste handling. The present system remains mostly inefficient, labor-intensive, and environmentally unsustainable even when rising levels of urbanization and consumption of resources increase waste production. This study examines the transformative potential of IoT technologies in developing intelligent data-driven solutions for waste management to solve critical infrastructure challenges in urban centers. This study developed IoT-enabled smart waste collection systems in three metropolitan areas using a comprehensive mixed-method approach that includes quantitative sensor data analysis, geospatial mapping, and longitudinal municipal waste tracking. Advanced sensor networks and associated machine learning algorithms were used to monitor volume, composition, and efficient collections of wastes. Predictive analytics and the edge computing framework were adapted to optimize routes for better waste collection, reduce associated operational costs, and hence also minimize the environmental footprint. The key results are possible savings of 37% in waste collection costs, an increase of 42% in route optimization for collections, and a reduction of several percent in greenhouse gas emissions due to smart routing and scheduling. IoT-led strategy outperformed conventional strategies for waste management with better operational efficiency, further signifying the revolutionary changes brought by digital technologies in managing urban infrastructure.

关键词： Waste management Waste handling Technological innovation Costs Urban planning Geospatial analysis Predictive analytics Sustainable development Optimization Edge computing

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Smart Drying technologies: A Case Study on Red Flesh Apple (Kissabel®) Using Computer Vision and Deep Learning

Smart Drying Technologies: A Case Study on Red Flesh Apple (...

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international Mid-Term conference of the Italian Association of Agricultural Engineering, MID-TERM AIIA 2024

作者： Benelli, Alessandro Pandolfi, Flavia Bandiera, Andrea Taormina, Eleonora Russo, Paola Adiletta, Giuseppina Massantini, Riccardo Moscetti, Roberto Department for Innovation in Biological Agro-Food and Forest Systems University of Tuscia Viterbo Italy Department of Chemical Engineering Materials Environment Sapienza University of Rome Rome Italy

ISBN: (纸本)9783031842115

Food drying is a crucial process that helps in enhancing the shelf-life of food at ambient temperature, also lowering transportation costs. However, erroneous applications can degrade product quality and lead to a significant energy consumption as common dryers use fossil fuels. The present study aims to develop a "smart" prototype hot-air dryer augmented with Computer Vision (CV) and Deep Learning (DL) technologies to monitor quality and drying status of red-flesh sliced apples (Malus domestica B. - cultivar Kissabel®) during the process. Both CV and DL represent Process Analytical Technology (PAT) tools that, combined with a Quality by Design (QbD) approach, can lead to real-time data from the process, which are potentially vital for understanding and controlling the drying dynamics of products. The experimentation was conducted on apple slices (approx. 5-mm thick) using the following drying parameters: drying time, 24 h;temperature, 35 ℃;R.H., 35%;and airflow, 3 m s−1. The "smart" drying system consisted of (i) a CMOS digital camera;(ii) a LED illumination setup (4200 K);(iii) a load cell;(iv) an Arduino UNO microcontroller (master);(v) a Jumo Dicon Touch controller (slave);(vi) a temperature and R.H. sensor;and (vii) a Raspberry Pi 4 microcomputer. The open-source software Node-Red was used as an orchestrator for controlling devices, as well as acquiring and storing product features in real-time, such as weight, color, size, and shape of slices. All acquired images of apple slices were subjected to semantic segmentation using a deep learning model. With the slice shrinkage data obtained from semantic segmentation and the moisture data, time-independent moisture ratio prediction models were developed. The approach opens new perspectives for the use of CV and DL technologies in food drying. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： computer vision deep learning moisture red flesh apples shrinkage smart drying

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Real-time condition monitoring of a gearbox using Hall effect sensor 4

Real-time condition monitoring of a gearbox using Hall effec...

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4th Biennial international conference on Nascent technologies in Engineering, ICNET 2021

作者： Yelve, Nitesh P. Lobo, Yohann Deogire, Aditi Varghese, Joel Mathew Talha, Mohammed Fr. C. Rodrigues Institute of Technology Department of Mechanical Engineering Vashi400 703 India

ISBN: (纸本)9781728190617

Problems with a gearbox can be fatal, therefore vigilance is vital. A gearbox is a key component in power transmission in various applications. Excessive load conditions or prolonged use of a gearbox in high-speed race cars or heavy working machinery leads to faults such as misalignment, increase in backlash, vibration, etc. The present work focuses on developing a technique to detect and display gear misalignments and increase in gear backlash in a gear box in real-time. The data regarding various faults are obtained using the Hall Effect sensor. This data is processed by a microcontroller and the corresponding condition of the gear, either damaged or intact, is displayed to the user in real-time. A Maruti 800 vehicle gearbox is used for this research. DRV 5055-Q1 Hall effect sensor is used to detect the faults in gears such as lateral misalignment, angular misalignment, and backlash. The developed system is capable of monitoring a gearbox effectively in real-time without the need of human intervention. © 2021 IEEE.

关键词： Vibrations (mechanical)

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Quantitative Analysis and Optimization of sensor Deployment for Enhanced Activity Recognition in Smart Home Environments: A Multidimensional Approach to Data-Driven Intelligence and Efficiency in Universal Computing Spaces

Quantitative Analysis and Optimization of Sensor Deployment ...

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Advancements in Power, Communication and Intelligent Systems (APCI), international conference on

作者： Khalid Aziz Sakshi Dua Prabal Gupta Lovely Professional University Phagwara Punjab India

ISBN: (数字)9798350363289

ISBN: (纸本)9798350363296

This paper presents a comprehensive study on the enhancement of smart home automation and monitoring systems through the application of advanced activity recognition algorithms and sensor deployment optimization. We start by taking a CASAS dataset capturing a wide range of daily living activities, detected through an array of environmental sensors. This study conducts an in-depth analysis of activity recognition performance, leveraging precision, recall, and f1score metrics to identify areas for improvement in existing machine learning models. Further, we investigate sensor activation data to propose optimizations in sensor deployment, aimed at increasing the accuracy of activity recognition while reducing unnecessary sensor data processing. Through temporal analysis of activity patterns, we develop predictive models that forecast future activities with significant accuracy, facilitating smarter resource management and personalized automation strategies. This paper also explores the implications of our findings on user experience enhancement. Our methodology showcases the integration of machine learning techniques, statistical analysis, and practical considerations for deploying smart home technologies. The results indicate a promising avenue for future research and development in smart environments, with potential applications extending beyond residential settings to include healthcare facilities and office spaces. The findings underscore the importance of adaptive and intelligent systems in enhancing the quality of life through technology.

关键词： Adaptation models Automation Adaptive systems Statistical analysis Smart homes Machine learning Activity recognition

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A Novel Clustering protocol for Optimal Node Placement in Wireless sensor Networks

A Novel Clustering protocol for Optimal Node Placement in Wi...

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2021 international conference on Information Science and Communications technologies, ICISCT 2021

作者： Muzafarov, Farruh Eshmuradov, Abdimurod Kamola, Glopova Tashkent University of Information Technologies Named after Muhammad Al-Kwarizmi Department of Telecommunication Engineering Tashkent Uzbekistan

ISBN: (纸本)9781665432580

Over the past years, there have been several issues related to WSN. In this research, we analyzed the most advanced aspects like important characteristics, research parameters, energy conversation, network lifetime, practical issues and various challenges with Clustered wireless sensor networks. We propose clustering-based routing protocol for Wireless sensor network (CBWSN) to reduce energy consumption and improve energy efficiency through clustering and routing algorithms. The basic idea is to periodically update the network topology and select the node with larger degree and high residual energy as the cluster head to be responsible for data aggregation and transmission. With the nodes moving, joining, and choosing the optimal clustering radius, the energy load of the whole network can be evenly distributed to each sensor node, which can significantly prolong the network lifetime. Extensive simulations show that CBWSN is more energy-efficient than the existing protocols. © 2021 IEEE.

关键词： Routing protocols

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CSRR Integrated Microwave sensor for Analyte Dielectric Sensing

CSRR Integrated Microwave Sensor for Analyte Dielectric Sens...

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Mobile Networks and Wireless Communications (ICMNWC), IEEE international conference on

作者： G. Challa Ram S. Yuvaraj M. Venkata Subbarao P. Sai Sneha Department of ECE National Institute of Technology Andhra Pradesh India Department of ECE Shri Vishnu Engineering College for Women Bhimavaram A.P India

A microstrip patch antenna with Rectangular Complementary Split Ring Resonator (R-CSRR) for sensing applications is proposed in this paper. In recent years, due to the rapid growth of wireless communication systems and emerging technologies, there has been an increased need for microwave antenna designs that are both compact and efficient. This paper introduces an approach to enhance the performance of microstrip patch antennas through the integration of a RCSRR structure. The proposed design provides an operating frequency of 2.58 GHz and s-parameter magnitude of -21.35 dB. The design can act as a high sensitive microwave sensor to detect the dielectric constants of different analytes. Moreover, a range of machine learning regression algorithms have been utilized to accurately forecast the dielectric constant of the analyte by analyzing the frequency response of the sensor. The performance analysis reveals that polynomial regression exceeds other methods, demonstrating a minimal root mean squared error of 0.2948. These machine learning-driven techniques greatly improve the sensor's performance, making it a valuable asset for the future applications in biochemical sensing.

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THE SENSING PROPERTIES OF CARBON NANOTUBE FILLED COPOLYMERS FOR VOC VAPORS DETECTION 12

THE SENSING PROPERTIES OF CARBON NANOTUBE FILLED COPOLYMERS ...

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12th international conference on Nanomaterials - Research and Application (NANOCON)

作者： Slobodian, Rostislav Olejnik, Robert Matyas, Jiri Slobodian, Petr Tomas Bata Univ Zlin Ctr Polymer Syst Zlin Czech Republic

ISBN: (纸本)9788087294987

Nowadays, carbon nanotubes are a widely available material, especially multiwall carbon nanotubes. In addition to many other applications, they find use in all kinds of sensors, like deformation, motion, tensile and pressure responsive elements. Numerous applications in sensors for volatile organic compounds (VOCs) are reported as well, nevertheless, they mainly suffer from low selectivity. Therefore, in this research, a sensor containing MINCNTs dispersed in a functional polymer matrix was prepared. As a polymer matrix, styrene-isoprenestyrene elastomer was chosen. The standard sensing mechanism of entangled MINCNTs is based on the quality of the contacts (charge transfer) between the individual nanotubes. In the prepared nanocomposite, the mechanism is modified due to the presence of the otherwise non-conductive matrix. The changes of conductivity depend on the response of the percolating nanotube filler network to the swelling of the polymer matrix due to adsorption of VOCs. The tested gas substances have high values of diffusion coefficient for the polymer, so they have a quick response. Then, the selectivity is ensured by differences in solubility of the tested VOCs in the polymer. The effect was demonstrated for four VOCs differing by their affinity to the polymer matrix, namely, heptane, toluene, acetone, and ethanol.

关键词： Carbon nanotubes copolymer nanocomposite organic vapour sensing gas sensor

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