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检索条件"任意字段=IEEE International Conference on Distributed Computing Systems"

共 149975 条记录，以下是731-740 订阅

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OEDASA: Optimization Enabled Error-Diluted Approximate Systolic Array Design for an Image Processing Application 37

OEDASA: Optimization Enabled Error-Diluted Approximate Systo...

引用

37th international conference on VLSI Design (VLSID) / 23rd international conference on Embedded systems (ES)

作者： Devi, Dantu Nandini Kumar, Gandi Ajay Gowda, Bindu G. Rao, Madhav IIIT Bangalore Bangalore Karnataka India

ISBN: (纸本)9798350384406

Systolic Array (SA) architecture is a hardware accelerator for running Artificial Intelligence (AI) workloads. Although approximate computing offers hardware and performance benefits, it often sacrifices accuracy, limiting its application to error-resilient tasks. Many inexact multipliers in SA exhibit one-sided Error Distribution (ErD), resulting in significant accumulated errors. Approximate computing proves valuable in error-resilient image processing applications, fostering research into various approximation techniques for enhanced hardware performance. This paper explores SA architecture with different configurations of approximate multipliers (AMs) featuring distinct ErDs. It employs a meta-heuristic optimization algorithm, Particle Swarm Optimization (PSO), for image smoothing tasks. The study delves into trade-offs between hardware acceleration and accuracy, offering insights for advancing approximate computing in SA-based AI workloads. The PSO-evolved SA configuration showcases a 3.05% performance improvement, 10.63% silicon footprint reduction, and 10.32% power savings compared to the exact SA. The PSO-derived SA structure also offers notable hardware gains when compared with other state-of-theart (SOTA) benchmark designs. Additionally, it demonstrates a better Structural Similarity Index (SSIM) compared to SA with one-sided error-distributed AMs. The proposed spatially optimized SAs with AMs of different ErDs represent a step towards reliable hardware design and establishing a nearly exact AI accelerator system. All design files and results are shared openly with the research and design community for easy adoption and further exploration.

关键词： Systolic Array Convolution Approximate computing Image Processing Particle Swarm Optimisation (PSO)

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Research on Cloud computing Security Based on Virtualization Security Technology 4

Research on Cloud Computing Security Based on Virtualization...

引用

4th international conference on Information Science, Parallel and distributed systems, ISPDS 2023

作者： Dang, Fangfang Yang, Ying Liu, Han Li, Dingding State Grid Henan Information & Telecommunication Company Henan Zhengzhou China

ISBN: (纸本)9798350337181

In order to overcome the problems of high intrusion rate and low encryption depth of traditional cloud computing security research methods, this paper proposes a new cloud computing security research method based on Virtualization security technology. First, analyze the principle of virtualization technology, and build a cloud computing resource transmission model to understand the whole cloud computing process. Secondly, the chaotic mapping method is used to transform cloud computing data to obtain binary chaotic sequence data, and realize the security encryption of cloud computing data to further ensure the security of cloud computing data. Finally, build the cloud computing data encryption and decryption algorithm to complete the cloud computing security research. Experimental results show that compared with traditional methods, the proposed method can effectively improve the security of cloud computing and reduce the intrusion rate. © 2023 ieee.

关键词： Cryptography

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Open Architecture for distributed and Cooperative Media Algorithms 3

Open Architecture for Distributed and Cooperative Media Algo...

引用

3rd international conference for Innovation in Technology, INOCON 2024

作者： Bhambu, Pawan Manjunatha, R. Srivastava, Pratima Vivekananda Global University Department of Computer Science and Engineering Jaipur India School of Sciences Department of Data Analytics and Mathematical Sciences Karnataka Bangalore India Arka Jain University Department of Biotechnology Jharkhand Jamshedpur India

ISBN: (纸本)9798350381931

The Open structure for allotted and Cooperative Media Algorithms (OADCMA) is an open-deliver framework imparting a plug-in platform that lets customers, without problem, develop distributed and cooperative media algorithms to utilize the computational assets of diverse heterogeneous structures. It's miles designed for operations along with video capture, transmission, and machine operations. OADCMA affords unified APIs for allotted and cooperative media algorithms, which simplifies the implementation of distributed and cooperative media algorithms. Additionally, OADCMA permits green parallel computing while averting scalability problems. OADCMA helps a widespread fashion of verbal exchange networks, including allotted finite discipline computing. It is appropriate for an extensive kind of allotted and cooperative media programs together with video surveillance and broadcasting. © 2024 ieee.

关键词： Security systems

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Task Integrity Checker: A Block Chain - Enabled Trust Management System for Fog Nodes 20

Task Integrity Checker: A Block Chain - Enabled Trust Manage...

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20th ieee international Wireless Communications and Mobile computing (ieee IWCMC) - Green and Intelligent Communications

作者： Rasagna, V Geethakumari, G. Shah, Jinil Bhavin Chaudhari, Nisarg Bits Pilani Dept CSIS Hyderabad India Bits Pilani Dept EEE Hyderabad India

ISBN: (纸本)9798350361261;9798350361278

Fog computing, a transformative computational paradigm, has ushered in new opportunities but also introduced significant security challenges. This paper presents a vital trust-based framework called Task Integrity Checker in Fog computing systems (TICS) to address these challenges, mainly focusing on mitigating On-Off attacks in the fog computing environment. An On-Off attack is a threat where attackers strategically alternate between malicious and benign behaviors, exploiting temporary errors to evade conventional detection methods. Detecting and thwarting such attacks is imperative for safeguarding the integrity and reliability of fog systems. Our proposed approach tackles this challenge by continuously monitoring and updating trust values for fog nodes based on task results and past performance. These trust values are securely stored in a blockchain, ensuring immutability and enhancing TICS's overall security. Utilizing blockchain technology bolsters the effectiveness of our solution, as it provides a tamper-resistant foundation for trust computation and attack mitigation. We rigorously evaluate the performance of our solution through comprehensive simulation experiments, assessing its effectiveness under various scenarios, including fluctuations in the number of fog nodes and varying attack intensities. The results affirm the efficacy of our approach in detecting and mitigating On-Off attacks, ultimately strengthening the security posture of fog computing systems. This solution is practical and adaptable to diverse fog computing scenarios, making it a valuable addition to security measures in this dynamic and evolving domain.

关键词： Fog computing On-Off Attack Trust BlockChain

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AMBIT: An Efficient Pruning Technique in Federated Learning for Edge computing systems 8

AMBIT: An Efficient Pruning Technique in Federated Learning ...

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8th ieee international conference on Fog and Edge computing (ICFEC)

作者： Hammam, Emad H. Guan, Peiyuan Taherkordi, Amir Shahraki, Amin Lan, Dapeng Univ Oslo Oslo Norway Shenyang Inst Automat Shenyang Peoples R China

ISBN: (纸本)9798350361360;9798350361353

The Industrial Internet of Things (IIoT) has revolutionized industrial sectors with enhanced connectivity, data exchange, and predictive maintenance. However, it faces various challenges from non-IID data distributions and communication overheads, to the consistency and privacy of prediction models for maintenance. Federated Learning (FL) has been considered as a prevalent technique to address privacy concerns. On the other hand, Edge computing (EC) is being increasingly introduced to ensure low-latency data processing in IIoT systems, especially those with time-critical requirements, e.g., industrial robotics and motion control systems. Moreover, the complexity and design dimensions of today's IIoT systems has lead to the development of large Machine Learning (ML) models with millions of parameters, e.g., using computer vision for field management. This introduces computational and privacy challenges in IIoT scenarios. Innovative FL optimization approaches such as pruning are aimed to tackle these challenges by reducing the number of training parameters, while they may impact accuracy. In this paper, we propose a new technique, called Adaptive Mean aBsolute devIaTion (AMBIT), which is an innovative pruning approach optimizing data transmission without compromising model accuracy and inducing additional computation overhead. By dynamically comparing the difference between the current and the previous weight value, AMBIT adapts better to parameter fluctuations at different stages, thereby accurately locating those parameters that have less impact on convergence. AMBIT's generality and efficiency are illustrated using MNIST and CIFAR-10 datasets, outperforming traditional Magnitude pruning in FL. For MNIST, AMBIT reduces data uploads up to 43.75%, with an increase of 0.62% in accuracy. While for For CIFAR-10, AMBIT achieved a 63.44% decrease with a 5.22% drop in accuracy.

关键词： Federated Learning Edge computing Industrial Internet of Things Pruning Techniques

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Hierarchical ADP Operation Strategy of distributed Energy Storage for Demand Management and Frequency Response Service 4

Hierarchical ADP Operation Strategy of Distributed Energy St...

引用

4th international conference on Intelligent Power and systems, ICIPS 2024

作者： Wen, Kerui Li, Weidong Zhang, Tingting Lv, Yanqi Nanjing University School of Management & Engineering Nanjing China Dalian University of Technology School of Electrical Engineering Dalian China

ISBN: (纸本)9798331532765

A hierarchical approximate dynamic programming (ADP) strategy is presented to determine intra-day operations of distributed energy storage cluster for demand management and frequency response service. According to the principle of decomposition coordination, the intra-day operation problem is divided into cluster scheduling layer, subcluster control layer and terminal response layer, wherein a flexible allocation mechanism of primary frequency response (PFR) reserve is devised. The hybrid lookahead, myopic allocation and automatic control methods are adopted to achieve global coordination of cluster, local control of subcluster and automatic response of terminal. The results show that the proposed strategy can ensure the economic benefit and PFR service within a short computing time. Moreover, the flexible allocation mechanism can increase resource utilization and operational precision. © 2024 ieee.

关键词： Demand response

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Evaluating an Analog Main Memory Architecture for All-Analog In-Memory computing Accelerators 6

Evaluating an Analog Main Memory Architecture for All-Analog...

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6th international conference on AI Circuits and systems (AICAS)

作者： Adam, Kazybek Monga, Dipesh Numan, Omar Singh, Gaurav Halonen, Kari Andraud, Martin Aalto Univ Dept Elect & Nanoengn Espoo Finland UC Louvain ICTEAM Louvain Belgium

ISBN: (纸本)9798350383638;9798350383645

Analog in memory computing (IMC) has emerged as a promising method to accelerate deep neural networks (DNNs) on hardware efficiently. Yet, analog computation typically focuses on the multiply and accumulate operation, while other operations are still being computed digitally. Hence, these mixed-signal IMC cores require extensive use of data converters, which can take a third of the total energy and area consumption. Alternatively, all-analog DNN computation is possible but requires increasingly challenging analog storage solutions, due to noise and leakage of advanced technologies. To enable all-analog DNN acceleration, this work demonstrates a feasible IMC architecture using an efficient analog main memory (AMM) cell. The proposed AMM cell is 42x and 5x more power and area efficient than a baseline analog storage cell. An all-analog architecture using this cell achieves potential efficiency gains of 15x compared with a mixed-signal IMC core using data converters.

关键词： Analog in memory computing Analog Memory

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Exploring the linkage between partition-based distributed extended Kalman filter and distributed full-information estimation 7

Exploring the linkage between partition-based distributed ex...

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ieee 7th international conference on Industrial Cyber-Physical systems (ICPS)

作者： Li, Xiaojie Yin, Xunyuan Nanyang Technol Univ Sch Chem Chem Engn & Biotechnol 62 Nanyang Dr Singapore 637459 Singapore

ISBN: (纸本)9798350363029;9798350363012

In this paper, we revisit a partition-based distributed extended Kalman filter (DEKF) method proposed in [1] for continuous-time nonlinear systems. Our objective is to offer a comprehensive perspective on the development of this DEKF method, elucidating its relationship with partition-based distributed full-information estimation within a discrete-time linear framework. Specifically, we present a partition-based distributed full-information estimation formulation for discrete-time linear systems. We derive an analytical solution for this full-information estimation problem which is in the form of a partition-based distributed Kalman filter (DKF). The DKF approach is extended to address nonlinear systems through successive linearization of nonlinear subsystem models, and a discrete-time distributed extended Kalman filter (DEKF) approach is derived. We compare the derived discrete-time DEKF with the continuous-time DEKF approach in [1] to reveal the connection between the DEKF approach in [1] and the distributed full-information estimation in a discrete-time context. A simulated process is utilized to verify the effectiveness and assess the performance of the distributed extended Kalman filter.

关键词： distributed state estimation partition-based framework extended Kalman filter nonlinear process

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Mitigating synchronization bottlenecks in high-performance actor-model-based software

Mitigating synchronization bottlenecks in high-performance a...

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2024 Workshops of the international conference for High Performance computing, Networking, Storage and Analysis, SC Workshops 2024

作者： Klenk, Kyle Moayeri, Mohammad Mahdi Guo, Junwei Clark, Martyn P. Spiteri, Raymond J. University of Saskatchewan Department of Computer Science Saskatoon Canada University of Calgary Department of Civil Engineering Calgary Canada

ISBN: (纸本)9798350355543

Bulk synchronous programming (in distributed-memory systems) and the fork-join pattern (in shared-memory systems) are often used for problems where independent processes must periodically synchronize. Frequent synchronization can greatly undermine the performance of software designed to solve such problems. We use the actor model of concurrent computing to balance the load of hundreds of thousands of short-lived tasks and mitigate synchronization bottlenecks by buffering communication via actor batching. The actor model is becoming increasingly popular in scientific and high-performance computing because it can handle heterogeneous tasks and computing environments with enhanced programming flexibility and ease relative to conventional paradigms like MPI. For a hydrologic simulation of continental North America with over 500,000 elements, the proposed buffering approach is approximately 4 times faster than no buffering, outperforms MPI on single and multiple nodes, and remains competitive with OpenMP on a single node and MPI+OpenMP on multiple nodes. © 2024 ieee.

关键词： actor model of concurrent computing bulk synchronous programming fork-join pattern high-throughput computing scientific and high-performance computing

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E2C: A Visual Simulator to Reinforce Education of Heterogeneous computing systems

E2C: A Visual Simulator to Reinforce Education of Heterogene...

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37th ieee international Parallel and distributed Processing Symposium (IPDPS)

作者： Mokhtari, Ali Rawls, Drake Huynh, Tony Green, Jeremiah Salehi, Mohsen Amini Univ Louisiana Lafayette Sch Comp & Informat High Performance Cloud Comp HPCC Lab Lafayette LA 70503 USA

ISBN: (纸本)9798350311990

Heterogeneity has been an indispensable aspect of distributed computing throughout the history of these systems. In particular, with the increasing popularity of accelerator technologies (e.g., GPUs and TPUs) and the emergence of domain-specific computing via ASICs and FPGA, the matter of heterogeneity and understanding its ramifications on the system performance has become more critical than ever before. However, it is challenging to effectively educate students about the potential impacts of heterogeneity on: (a) the performance of distributed systems;and (b) the logic of resource allocation methods to efficiently utilize the resources. Making use of the real infrastructure (such as those offered by the public cloud providers) for benchmarking the performance of heterogeneous machines, for different applications, with respect to different objectives, and under various workload intensities is cost- and time-prohibitive. Moreover, not all students (globally and nationally) have access or can afford such real infrastructure. To reinforce the quality of learning about various dimensions of heterogeneity, and to decrease the widening gap in education, we develop an open-source simulation tool, called E2C, that can help students researchers and practitioners to study any type of heterogeneous (or homogeneous) computing system and measure its performance under various system configurations. To make the learning curve shallow, E2C is equipped with an intuitive graphical user interface (GUI) that enables its users to easily examine system-level solutions (scheduling, load balancing, scalability, etc.) in a controlled environment within a short time and at no cost. In particular, E2C is a discrete event simulator that offers the following features: (i) simulating a heterogeneous computing system;(ii) implementing a newly developed scheduling method and plugging it into the system, (iii) measuring energy consumption and other output-related metrics;and (iv) powerful visual a

关键词： Cloud computing Heterogeneous computing systems Learning Tool Simulator Workload Generator

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