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arXiv 2022年

作者： Frank, Daniel Latif, Decky Aspandi Muehlebach, Michael Unger, Benjamin Staab, Steffen Institute for Parallel and Distributed Systems University of Stuttgart Germany Max Planck Institute for Intelligent Systems Germany Stuttgart Center for Simulation Science Germany Institute for Parallel and Distributed Systems University of Stuttgart and Electronics and Computer Science University of Southampton United Kingdom

Recurrent neural networks are capable of learning the dynamics of an unknown nonlinear system purely from input-output measurements. However, the resulting models do not provide any stability guarantees on the input-output mapping. In this work, we represent a recurrent neural network as a linear time-invariant system with nonlinear disturbances. By introducing constraints on the parameters, we can guarantee finite gain stability and incremental finite gain stability. We apply this identification method to learn the motion of a four-degrees-of-freedom ship that is moving in open water and compare it against other purely learning-based approaches with unconstrained parameters. Our analysis shows that the constrained recurrent neural network has a lower prediction accuracy on the test set, but it achieves comparable results on an out-of-distribution set and respects stability conditions. © 2022, CC BY.

关键词： Recurrent neural networks

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Simulating Cyber Attacks and Designing Malware using Python 10

Simulating Cyber Attacks and Designing Malware using Python

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10th International Conference on Signal Processing and Integrated Networks, SPIN 2023

作者： Ankit, Akash Inder, Shubham Sharma, Anuj Johari, Rahul Vidyarthi, Deo Prakash University School of Information Communication and Technology Guru Gobind Singh Indraprastha University SWINGER: Security Wireless IoT Network Group of Engineering and Research Dwarka New Delhi110078 India MelbourneVIC3000 Australia Jawaharlal Nehru University Parallel and Distributed System Lab School of Computer and Systems Sciences New Delhi110067 India

ISBN: (纸本)9781665490993

In this Internet era, we have become heavily dependent on the World Wide Web and it has become a basic amenity for humans. A normal user can be trapped easily in this vicious web if not careful enough. It is a field that requires users to be on their toes every time they try to connect to this enormous interconnection of networks. Reports and Surveys have said that in the coming years, Cybercrime could become the biggest threat. In this proposed work, the authors have deployed applications and designed malware for the purpose of simulating various kinds of cyber-attacks so that they could study their effects & affects and ultimately devise solutions to resolve the vulnerabilities in a system. These applications included networking concepts & protocols and a software based keylogger which was developed with no malicious intent, but to analyse the architectural view or design of a malware and to study the stages of a malware attack like entry, distribution, exploitation, infection and execution. Efforts have been made to demonstrate spooting attacks with an idea of identifying vulnerabilities and security loopholes in a particular system that can be exploited by an attacker if not resolved within time. © 2023 IEEE.

关键词： Network security

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A survey of script learning

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Frontiers of Information Technology & Electronic Engineering 2021年第3期22卷 341-373页

作者： Yi HAN Linbo QIAO Jianming ZHENG Hefeng WU Dongsheng LI Xiangke LIAO Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense TechnologyChangsha 410000China Science and Technology on Information Systems Engineering Laboratory National University of Defense TechnologyChangsha 410000China School of Data and Computer Science Sun Yat-sen UniversityGuangzhou 510006China

Script is the structured knowledge representation of prototypical real-life event *** the commonsense knowledge inside the script can be helpful for machines in understanding natural language and drawing commonsensible *** learning is an interesting and promising research direction,in which a trained script learning system can process narrative texts to capture script knowledge and draw ***,there are currently no survey articles on script learning,so we are providing this comprehensive survey to deeply investigate the standard framework and the major research topics on script *** research field contains three main topics:event representations,script learning models,and evaluation *** each topic,we systematically summarize and categorize the existing script learning systems,and carefully analyze and compare the advantages and disadvantages of the representative *** also discuss the current state of the research and possible future directions.

关键词： Script learning Natural language processing Commonsense knowledge modeling Event reasoning

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Training Large Language Models for System-Level Test Program Generation Targeting Non-functional Properties

Training Large Language Models for System-Level Test Program...

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IEEE European Test Symposium (ETS)

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)9798350349320

ISBN: (纸本)9798350349337

System-Level Test (SLT) has been an integral part of integrated circuit test flows for over a decade and continues to be significant. Nevertheless, there is a lack of systematic approaches for generating test programs, specifically focusing on the non-functional aspects of the Device under Test (DUT). Currently, test engineers manually create test suites using commercially available software to simulate the end-user environment of the DUT. This process is challenging and laborious and does not assure adequate control over non-functional properties. This paper proposes to use Large Language Models (LLMs) for SLT program generation. We use a pre-trained LLM and fine-tune it to generate test programs that optimize non-functional properties of the DUT, e.g., instructions per cycle. Therefore, we use Gem5, a microarchitectural simulator, in conjunction with Reinforcement Learning-based training. Finally, we write a prompt to generate C code snippets that maximize the instructions per cycle of the given architecture. In addition, we apply hyperparameter optimization to achieve the best possible results in inference.

关键词： Training Knowledge engineering Codes Systematics Microarchitecture Process control Hyperparameter optimization

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Scalable Infrastructure for Workload Characterization of Cluster Traces

arXiv

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arXiv 2022年

作者： van Loo, Thomas Jindal, Anshul Benedict, Shajulin Chadha, Mohak Gerndt, Michael Computer Architecture and Parallel Systems Technical University Munich Germany Indian Institute of Information Technology Kerala Kottayam India

In the recent past, characterizing workloads has been attempted to gain a foothold in the emerging serverless cloud market, especially in the large production cloud clusters of Google, AWS, and so forth. While analyzing and characterizing real workloads from a large production cloud cluster benefits cloud providers, researchers, and daily users, analyzing the workload traces of these clusters has been an arduous task due to the heterogeneous nature of data. This article proposes a scalable infrastructure based on Google’s dataproc for analyzing the workload traces of cloud environments. We evaluated the functioning of the proposed infrastructure using the workload traces of Google cloud cluster-usage-traces-v3. We perform the workload characterization on this dataset, focusing on the heterogeneity of the workload, the variations in job durations, aspects of resources consumption, and the overall availability of resources provided by the cluster. The findings reported in the paper will be beneficial for cloud infrastructure providers and users while managing the cloud computing resources, especially serverless platforms. © 2022, CC BY.

关键词： Cluster computing

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Large Language Models to Generate System-Level Test Programs Targeting Non-functional Properties

arXiv

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arXiv 2024年

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

System-Level Test (SLT) has been a part of the test flow for integrated circuits for over a decade and still gains importance. However, no systematic approaches exist for test program generation, especially targeting non-functional properties of the Device under Test (DUT). Currently, test engineers manually compose test suites from off-the-shelf software, approximating the end-user environment of the DUT. This challenging and tedious task does not guarantee sufficient control over non-functional properties. This paper proposes Large Language Models (LLMs) to generate test programs. We take a first glance at how pre-trained LLMs perform in test program generation to optimize nonfunctional properties of the DUT. Therefore, we write a prompt to generate C code snippets that maximize the instructions per cycle of a super-scalar, out-of-order architecture in simulation. Additionally, we apply prompt and hyperparameter optimization to achieve the best possible results without further training. © 2024, CC BY.

关键词： Software testing

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A Novel Evaluation Strategy to Artificial Neural Network Model Based on Bionics

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Journal of Bionic Engineering 2022年第1期19卷 224-239页

作者： Sen Tian Jin Zhang Xuanyu Shu Lingyu Chen Xin Niu You Wang School of Mathematics and Statistics Hunan Normal UniversityChangsha410081China College of Information Science and Engineering Hunan Normal UniversityChangsha410081China School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China Key Laboratory of Industrial Control Technology Zhejiang UniversityHangzhou310058China Science and Technology on Parallel and Distributed Laboratory College of ComputerNational University of Defense TechnologyChangsha410199China Key Laboratory of Industrial Control Technology Institute of Cyber Systems and ControlZhejiang UniversityHangzhou310027China

With the continuous deepening of Artificial Neural Network(ANN)research,ANN model structure and function are improving towards diversification and ***,the model is more evaluated from the pros and cons of the problem-solving results and the lack of evaluation from the biomimetic aspect of imitating neural networks is not inclusive ***,a new ANN models evaluation strategy is proposed from the perspective of bionics in response to this problem in the ***,four classical neural network models are illustrated:Back Propagation(BP)network,Deep Belief Network(DBN),LeNet5 network,and olfactory bionic model(KIII model),and the neuron transmission mode and equation,network structure,and weight updating principle of the models are analyzed *** analysis results show that the KIII model comes closer to the actual biological nervous system compared with other models,and the LeNet5 network simulates the nervous system in ***,evaluation indexes of ANN are constructed from the perspective of bionics in this paper:small-world,synchronous,and chaotic ***,the network model is quantitatively analyzed by evaluation indexes from the perspective of *** experimental results show that the DBN network,LeNet5 network,and BP network have synchronous *** the DBN network and LeNet5 network have certain chaotic characteristics,but there is still a certain distance between the three classical neural networks and actual biological neural *** KIII model has certain small-world characteristics in structure,and its network also exhibits synchronization characteristics and chaotic *** with the DBN network,LeNet5 network,and the BP network,the KIII model is closer to the real biological neural network.

关键词： Artificial neural network(ANN) Back Propagation(BP)network Deep Belief Network(DBN) LeNet5 network Olfactory bionic model(KIII model) Small world Chaos Synchronous

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

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

引用

IEEE International Symposium on Defect and Fault Tolerance in VLSI systems

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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Phase-field modeling and effective simulation of non-isothermal reactive transport

arXiv

引用

arXiv 2023年

作者： Bringedal, Carina Jaust, Alexander Department of Computer science Electrical engineering and Mathematical sciences Western Norway University of Applied Sciences Norway Institute for Modelling Hydraulic and Environmental Systems University of Stuttgart Germany Institute for Parallel and Distributed Systems University of Stuttgart Germany

We consider single-phase flow with solute transport where ions in the fluid can precipitate and form a mineral, and where the mineral can dissolve and release solute into the fluid. Such a setting includes an evolving interface between fluid and mineral. We approximate the evolving interface with a diffuse interface, which is modeled with an Allen-Cahn equation. We also include effects from temperature such that the reaction rate can depend on temperature, and allow heat conduction through fluid and mineral. As Allen-Cahn is generally not conservative due to curvature-driven motion, we include a reformulation that is conservative. This reformulation includes a non-local term which makes the use of standard Newton iterations for solving the resulting non-linear system of equations very slow. We instead apply L-scheme iterations, which can be proven to converge for any starting guess, although giving only linear convergence. The three coupled equations for diffuse interface, solute transport and heat transport are solved via an iterative coupling scheme. This allows the three equations to be solved more efficiently compared to a monolithic scheme, and only few iterations are needed for high accuracy. Through numerical experiments we highlight the usefulness and efficiency of the suggested numerical scheme and the applicability of the resulting *** Codes 35R37, 65M08, 65M22, 76D10, 76D05, 76V05, 80A32, 80M12 © 2023, CC BY.

关键词： Minerals

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Precise characterization of coherence activity in multicores using gem5

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Journal of Supercomputing 2025年第8期81卷

作者： Ferrer, Joaquín Cebrian, Juan M. Fernández-Pascual, Ricardo Acacio, Manuel E. Computer Architecture and Parallel Systems Group University of Murcia Murcia Spain

Simulation enables cost-effective and rapid prototyping in computer architecture research. It helps assess the impact of architectural changes on performance, area, and energy consumption, playing a crucial role in early-stage development. Gem5 has become a widely used simulation tool in academia and industry for researching multicore architectures. However, its accuracy depends on proper configuration. Key parameters, such as core microarchitecture, memory hierarchy, and interconnection network, must be carefully calibrated to ensure realistic results. This work highlights the importance of a well-adjusted simulation environment for modeling modern multicore setups, with a focus on coherence directory. We refine core, memory, and interconnection parameters, identifying and addressing deficiencies in the simulation infrastructure. We introduce new functionalities and statistics to enhance system characterization. We implement Intel’s top-down methodology in gem5, extending it with two new levels to analyze coherence activity’s impact on performance. Lastly, we enable gem5 to support various sparse directory architectures. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Memory architecture

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