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检索条件"任意字段=International Symposium on Software Engineering for Parallel and Distributed Systems"

共 10737 条记录，以下是431-440 订阅

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Control of Composite Manufacturing Processes Through Deep Reinforcement Learning 22

Control of Composite Manufacturing Processes Through Deep Re...

引用

22nd IEEE international Conference on Machine Learning and Applications, ICMLA 2023

作者： Stieber, Simon Heber, Leonard Obertscheider, Christof Reif, Wolfgang Institute for Software & Systems Engineering University of Augsburg Augsburg Germany University of Applied Sciences Wiener Neustadt Wiener Neustadt Austria

ISBN: (纸本)9798350345346

Resin transfer molding (RTM) is a composite manufacturing process that uses a liquid polymer matrix to create complex-shaped parts. There are several challenges associated with RTM. One of the main challenges is ensuring that the liquid polymer matrix is properly distributed throughout the composite material during the molding process. If the matrix is not evenly distributed, the resulting part may have weak or inconsistent properties. This is the challenge we tackle with the approach presented in this work. We implement an online control using deep reinforcement learning (RL) to ensure a complete impregnation of the reinforcing fibers during the injection phase, by controlling the input pressure on different inlets. This work uses this self-learning paradigm to actively control the injection of an RTM process, which has the advantage of depending on a reward function instead of a mathematical model, which would be the case for model predictive control. A reward function is more straightforward to model and can be applied and adapted to more complex problems. RL algorithms have to be trained through many iterations, for which we developed a simulation environment with a distributed and parallel architecture. We show that the presented approach decreases the failure rate from 54 % to 27 %, by 50 % compared to the same setup with steady parameters. © 2023 IEEE.

关键词： Control Reinforcement Learning Resin Transfer Molding

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Extending the Mochi Methodology to Enable Dynamic HPC Data Services

Extending the Mochi Methodology to Enable Dynamic HPC Data S...

引用

IEEE international symposium on parallel and distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Matthieu Dorier Philip Carns Robert Ross Shane Snyder Rob Latham Amal Gueroudji George Amvrosiadis Chuck Cranor Jerome Soumagne Argonne National Laboratory Carnegie Mellon University Intel Corporation

ISBN: (数字)9798350364606

ISBN: (纸本)9798350364613

High-performance computing (HPC) applications and workflows are increasingly making use of custom data services to complement traditional parallel file systems with fast transient data management capabilities tailored to application-specific needs. In the Mochi project we provide methodologies and tools that enable rapid development of custom HPC data services, including a collection of composable software components that can be combined to build complex distributed data services. Our initial version of Mochi targeted data services deployed with static configurations with a fixed number of nodes and minimal fault tolerance. However, there is a growing need for dynamic services that can adapt while running in response to changing workloads and system conditions. In this paper we present our work to extend the Mochi architecture to support the development of dynamic data services. We achieve this by providing new Mochi components that support unified bootstrapping and online reconfiguration, fault detection, monitoring, and consensus. We also provide a methodology for deriving service-wide resilience from the resilience of each of the service's components.

关键词： Productivity High performance computing distributed databases Authentication software Encryption Security

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The Art of Deception: Black-box Attack Against Text-to-Image Diffusion Model 29

The Art of Deception: Black-box Attack Against Text-to-Image...

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29th IEEE international Conference on parallel and distributed systems, ICPADS 2023

作者： Lu, Yuetong Xu, Jingyao Li, Yandong Lu, Siyang Wei, Xiang Lu, Wei Beijing Jiaotong University School of Software Engineering Beijing China Beijing Jiaotong University School of Computer and Information Technology Beijing China University of Central Florida Department of Computer Science OrlandoFL United States

ISBN: (纸本)9798350330717

With the rise of Foundation models, Text-to-Image models, as one of its important branches, have been increasingly applied. While focusing on the impressive generation capabilities of these models, it is also crucial to pay attention to the robustness of the models against attacks. In this paper, we shift our focus towards studying the vulnerability of Text-to-Image (T2I) models. To this end, we propose a black-box attack method and demonstrate that T2I models are susceptible to adversarial text attacks. Specifically, this method can disrupt T2I models by making subtle modifications to the model's input (i.e., prompt) without accessing the model parameters, resulting in the generation of incorrect images. It is worth mentioning that we discovered the ability to switch different types of tokenizers within this black-box framework to handle text, furthermore, this attack framework can be applied to target different versions of T2I models. The experiments indicate that the images generated through adversarial text exhibit noticeable errors. We also employ CLIP score, a metric used to evaluate the similarity between images and image descriptions, to assess the results. The findings demonstrate a significant decrease in the visual-textual similarity after the model is subjected to attacks. Additionally, we have identified a specific type of error that T2I models tend to make when facing attacks - when confronted with unrecognizable text, the model often interprets it as human-related content. This paper not only highlights the vulnerability of T2I models to adversarial text attacks but also further discusses potential methods that could enhance the robustness of these attack techniques. This provides a valuable reference for future research directions in this field. © 2023 IEEE.

关键词： Diffusion ModelAdversarial Attack Foundation Model Text-to-Image

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Research on Measuring Method of Function Size of Information System

Research on Measuring Method of Function Size of Information...

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software engineering, Artificial Intelligence, Networking and parallel/distributed Computing (SNPD-Winter), ACIS international Winter Conference on

作者： Du Chunye Shanghai Key Laboratory of Computer Software Testing &Evaluating Shanghai Development Center of Computer Software Technology Shanghai China

With the rapid development of software industry, a variety of new technologies are produced. Research and development in cloud computing, big data, artificial intelligence, the Internet of Things, blockchain, and other related fields continue to prosper. The increasing lines of code, function points, escalating scale of software systems, and the rising complexity of software development collectively complicate software cost estimation. This article studies how to estimate the size, workload, and cost of an information system using functional scale measurement methods.

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Heterogeneous Data Processing in All-Digital Phased Array Radar

Heterogeneous Data Processing in All-Digital Phased Array Ra...

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IEEE international symposium on Phased Array systems and Technology

作者： Skyler Garner Mark Yeary Advanced Radar Research Center University of Oklahoma Norman OK United States

ISBN: (数字)9798350392142

ISBN: (纸本)9798350392159

All-digital phased array radars are an emerging technology that require new data processing techniques which are scalable, rely on open-architecture software components, and do not create bottlenecks for the real-time operation. Achieving a solution for these issues relies on heterogeneous processing and distributed software development on CPUs and FPGAs, whereby the overarching algorithm processing chain is distributed in a way that begins at the ADC of each element on an array and concludes in actionable data products. An important aspect is not only the speed of the algorithms, but the throughput of the packetized data transfer. These packets are not only routed, but they are also acted upon in a network of computing services. Here, we explore an open-source resource manager, known as Kubernetes, which connects the packetized data with computing resources on the servers, i.e., moving data in and out of server RAM to complete algorithms such as creating range-Doppler maps, as our results section shows.

关键词： Phased arrays Array signal processing software algorithms Signal processing algorithms Radar parallel processing Throughput Arrays Servers software development management

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RSCache: A Tail Latency Friendly Cache Based on NVMe SSDs

RSCache: A Tail Latency Friendly Cache Based on NVMe SSDs

引用

international symposium on parallel and distributed Processing with Applications, ISPA

作者： Jincheng Lu Miao Cai Baoliu Ye College of Computer Science and Software Engineering Hohai University Nanjing China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

High fan-out requests are prevalent in systems employing multi-tier architectures. These requests are divided into several sub-requests for parallel processing. However, a high fan-out request must await all sub-requests to be completed before returning, but the processing times of sub-requests are unpredictable due to their differences in characteristics, such as data volume and data popularity. Meanwhile, existing SSD-based caches struggle to adjust request processing speeds to ensure timely handling. As a result, some sub-requests are delayed, affecting the overall latency and causing long tail latency *** paper proposes RSCache, a tail latency-friendly cache based on NVMe SSDs. RSCache combines the NVMe Weighted Round-robin (WRR) arbitration mechanism with a priority-based scheduling mechanism to enable differentiated request processing. We propose a fan-out size-based priority assignment strategy along with a latency-aware sub-request sorting method. They collaborate to prioritize sub-requests according to their impacts on tail latency and schedule them to NVMe priority queues with various processing speeds, effectively reducing the processing time variations among sub-requests. In addition, we balance the load across queues to avoid congestion with a novel feedback mechanism. We implement the prototype of RSCache based on SPDK. Our experiments demonstrate that RSCache reduces tail latency by up to 40% and improves throughput by two times compared to state-of-the-art SSD-based cache designs.

关键词： Schedules distributed processing Prototypes Tail parallel processing Throughput Sorting

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Large Language Model-Based Optimization for System-Level Test Program Generation

Large Language Model-Based Optimization for System-Level Tes...

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IEEE international symposium on Defect and Fault Tolerance in VLSI systems

作者： Denis Schwachhofer Peter Domanski Steffen Becker Stefan Wagner Matthias Sauer Dirk Pflüger Ilia Polian Institute of Computer Engineering and Computer Architecture University of Stuttgart Stuttgart Germany Institute of Software Engineering University of Stuttgart Stuttgart Germany Institute for Parallel and Distributed Systems University of Stuttgart Stuttgart Germany Technical University of Munich Heilbronn Germany Advantest Europe Boeblingen Germany

ISBN: (数字)9798350366884

ISBN: (纸本)9798350366891

System-Level Test (SLT) is essential for testing integrated circuits, focusing on functional and non-functional properties of the Device under Test (DUT). Traditionally, test engineers manually create tests with commercial software to simulate the DUT's end-user environment. This process is both time-consuming and offers limited control over non-functional properties. This paper proposes Large Language Models (LLMs) enhanced by Structural Chain of Thought (SCoT) prompting, a temperature schedule, and a pool of previously generated snippets to generate high-quality code snippets for SLT. We repeatedly query the LLM for a better snippet using previously generated snippets as examples, thus creating an iterative optimization loop. This approach can automatically generate snippets for SLT that target specific non-functional properties, reducing time and effort. Our findings show that this approach improves the quality of the generated snippets compared to unstructured prompts containing only a task description.

关键词： Measurement Schedules Codes Temperature Process control Very large scale integration software Optimization Nanotechnology Testing

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QMIMC: Q-Learning Model Based on Imperfect-information under Multi-agent Crowdtesting 19

QMIMC: Q-Learning Model Based on Imperfect-information under...

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19th IEEE international symposium on parallel and distributed Processing with Applications (IEEE ISPA)

作者： Zhang, Jie Li, Kefan Zhang, Baoming Xu, Ming Wang, Chongjun Nanjing Univ Dept Comp Sci & Technol State Key Lab Novel Software Technol Nanjing Peoples R China

ISBN: (纸本)9781665435741

Crowdtesting is one of the hot spots in artificial intelligence in recent years. Among which multi-agent crowdtesting system is a method to deal with the complex problems in crowdtesting process. How to improve the efficiency on the premise of ensuring the robustness of the system has become an urgent issue. This paper takes the task assignment in the crowdtesting process as the research background. On the basis of a single agent, this paper proposes a multi-agent collaboration framework and designs imperfect-information sharing mechanism by combining with Q -Learning and finally we optimized the algorithm. We performed relevant simulation experiments. Compared with traditional machine learning algorithms in indicators such as robustness and adaptability, our algorithm Q-Learning model based on imperfect-information under multiagent crowdtesting (QMIMC) had a good performance. In addition, this paper provides a certain reference for the application of multi-agent systems in crowdtesting systems.

关键词： Multi-Agent System Q-Learning Model Crowdsourcing System Imperfect-information

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OSN Rumor Control Model Based on Community Immunization

OSN Rumor Control Model Based on Community Immunization

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international symposium on parallel and distributed Processing with Applications, ISPA

作者： Ming Dong Zhiqiang Sun Zhenhua Tan Bin Zhang School of Computer Science and Engineering Northeastern University Shenyang China Software College Northeastern University Shenyang China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Shenyang China Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University) Ministry of Education China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

This paper proposes a rumor control model based on community immunization. Based on the community division and the trust network inference algorithm, the model redefines the standard to measure the importance of nodes in the network. First, the model uses the Louvain clustering algorithm based on the Ochiai coefficient to discover the network community and then presents the trust network inference algorithm. By analyzing the key factors that affect trust transfer between nodes, the trust evaluation between unfamiliar nodes is inferred, and important nodes with a high degree of trust in the network community are calculated. Finally, combined with the characteristics of inner degree and outer degree centrality of nodes in the network community, five types of important nodes in the network are screened out. To avoid repeated selection of nodes, this paper identifies a group of key nodes in the network community for local immunization by means of deduplication and taking intersection, so as to realize effective control of rumors in the network.

关键词： distributed processing Clustering algorithms Inference algorithms Standards Open data

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An Efficient Flow Rule Conflict Comprehensive Detection Scheme for SDN Networks

An Efficient Flow Rule Conflict Comprehensive Detection Sche...

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international symposium on parallel and distributed Processing with Applications, ISPA

作者： Bo Han Yuan Liu Yongbin Zhou Yiwen Gao School of Cyber Science and Engineering Nanjing University of Science and Technology Nanjing China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

software-Defined Networking (SDN) has introduced flexibility and efficiency to network management but also faces challenges from flow rule conflicts, including static, dynamic, and dependency conflicts. Existing detection algorithms often focus on a single conflict type, resulting in inefficiencies and high false positive rates. To address these issues, we propose a comprehensive flow rule conflict detection scheme that improves real-time detection of explicit conflicts (both static and dynamic) and reduces false positives in implicit (dependency) conflict detection. Specifically, we present a real-time explicit conflict detection algorithm based on the Protocol-Divided Trie (PDT), which categorizes flow rules by protocol type and uses a prefix tree for rapid matching. Experimental results show that this approach significantly reduces detection times by at least 39.2% and achieves 100% detection accuracy. Additionally, we propose a two-stage detection (TSD) algorithm that combines the precision of path-based detection (PBD) with the efficiency of alias set-based detection (ASD). Our experiments reveal a 51% reduction in false positives compared to ASD and a 48% reduction in detection time compared to PBD, while maintaining equivalent false positive rates. This approach provides a robust solution for conflict detection in SDN, improving network security and resource utilization efficiency.

关键词： distributed processing Protocols Accuracy Network security Real-time systems Resource management software defined networking Detection algorithms Faces

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