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检索条件"机构=National Laboratory for Parallel and Distributed Computing"

共 172 条记录，以下是91-100 订阅

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Agent oriented programming based on SLABS

Agent oriented programming based on SLABS

引用

IEEE Annual International Computer Software and Applications Conference (COMPSAC)

作者： Ji Wang Rui Shen Hong Zhu National Laboratory for Parallel and Distributed Processing Changsha China Department of Computing Oxford Brookes University Oxford UK

SLABS is a formal specification language designed for modular and composable specification of multi-agent systems. This paper reports our attempts to support SLABS at the level of programming languages. A programming language, SLABSp, is presented to support two distinguished mechanisms, namely caste and scenario, in caste-centric methodology of agent-oriented software development. Based on Java platform, the SLABSp has been implemented by compiling the programs into Java with the multi-agent runtime environment.

关键词： Slabs Computer languages Multiagent systems Programming Java Formal specifications Application software Protocols Laboratories distributed processing

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Temporal Closing Path for PLM-based Temporal Knowledge Graph Completion

Temporal Closing Path for PLM-based Temporal Knowledge Graph...

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International Joint Conference on Neural Networks (IJCNN)

作者： Xin Zhou Yongxue Shan Zixuan Dong Haijiao Liu Xiaodong Wang National Key Laboratory of Parallel and Distributed Computing College of Computer Science and Technology National University of Denfense Technology Changsha China

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Temporal Knowledge Graph Completion (TKGC) aims to predict missing parts of quadruples, which is crucial for real-life knowledge graphs. Compared with methods that only use graph neural networks, the emergence of pre-trained model has introduced a trend of simultaneously leveraging text and graph structure information. However, most current methods based on pre-trained models struggle to effectively utilize both text and multi-hop graph structure information concurrently, resulting in insufficient association mining of relations. To address the challenge, we propose a novel model: Temporal Closing Path for Pre-trained Language Model-based TKGC (TCP-PLM). We obtain the temporal closing relation path of the target relation through sampling, and use the relation path as a bridge to simultaneously utilize text and multi-hop graph structure information. Moreover, the relation path serves as a tool for mining associations between relations. At the same time, due to the design of entity-independent relation paths, our model can also handle the inductive setting. Our experiments on three benchmarks, along with extensive analysis, demonstrate that our model not only achieves substantial performance enhancements across four metrics compared to other models but also adeptly handles inductive settings.

关键词： Training Measurement Knowledge engineering Bridges Analytical models Knowledge graphs Transforms

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An experimental study of the emergent behaviors of self-organized agent communities

An experimental study of the emergent behaviors of self-orga...

引用

Congress on Evolutionary Computation

作者： Shufeng Wang Hong Zhu National Laboratory for Parallel and Distributed Processing Changsha China Department of Computing Oxford Brookes University Oxford UK

Emergent behavior is an essential feature in multi-agent systems and plays a significant role in the applications of agent technology. Because of the huge gap between individual agents' behaviors and those of the whole system, specifying and reasoning about emergent behaviors are notoriously difficult. Simulation has been the essential method to study emergent behaviors in multi-agent systems. In this paper, we report an experimental study of the emergent behaviors of self-organized agent communities, in which emergent behaviors play a crucial role. The experiments confirmed the results of a theoretical analysis of agent communities using a formal theory called scenario calculus. It further provided insight into the dynamic features of the system that were very difficult to obtain by using formal logic, such as the speed of convergence to the emergent states and the relationships between the convergence time and various parameters of self-organized agent communities systems.

关键词： Evolutionary computation

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Scenario mechanism in agent-oriented programming

Scenario mechanism in agent-oriented programming

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Asia-Pacific Conference on Software Engineering

作者： Rui Shen Ji Wang H. Zhu National Laboratory for Parallel and Distributed Processing Changsha China Department of Computing Oxford Brookes University Oxford UK

Scenario has been used to describe agent behaviors in the context of environment situations in the specification languages for agent-based systems, such as SLABS. It becomes an important language facility in the declaration of an agent for specifying its behaviors in its environment. Therefore, towards agent-oriented programming, it is necessary to introduce and implement scenario mechanism in programming languages. This paper reports our attempts to support the language facility from the view of programming languages, and presents an approach to facilitating the scenario mechanism in agent-oriented programming. The basic idea is to extend object-oriented programming language to support agent-oriented programming, where Java is chosen as the base language. Firstly, the language framework of agent-oriented programming, SLABSp is presented, mostly conforming to SLABS, whose syntax is extended based on Java. Scenario mechanism is introduced as the new feature in the programming language. Secondly, the underlying object models are defined to serve as the semantics of the language, where agents are modeled by a couple of objects. A compiler has been built to compile the agent-oriented programs into Java. A running platform has been constructed as the multiagent runtime environment of SLABSp.

关键词： Slabs Computer languages Java Object oriented modeling Object oriented programming Multiagent systems Specification languages Program processors Runtime environment Formal specifications

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OLM2: Automatic Optimal Strategy Generating for Large-Scale Model Training with Limited-Memory

OLM2: Automatic Optimal Strategy Generating for Large-Scale ...

引用

IEEE International Conference on Joint Cloud computing (JCC)

作者： Zhilin Yang Yu Tang Linbo Qiao Xi Yang Zhen Huang National Key Laboratory of Parallel and Distributed Computing College of Computer Science National University of Defense Technology Changsha 410073 China

The scale of model parameters and the amount of training data is exponentially increasing. It requires more GPU memory with the exponential increasement of model parameters. Recomputation and swapping are two main memory optimization methods that have been extensively studied, and there are also optimization strategies that combine the two methods. However, most of them are based on heuristic search strategies, which do not explore the complete solution space and can’t guarantee the optimality of the solution results. An optimal search strategy with tensor-level recomputation and swapping is expected in large-scale model training. In this paper, we propose an optimal strategy searching algorithm combining tensor-based recomputation and swapping. Specifically, the memory swapping strategy is reformulated as an optimization problem, which converts the memory constraints into mixed integer programming, to find the optimal memory optimization strategy. By leveraging the advantages of both recomputation and swapping, this approach minimizes computation consumption without exceeding the available memory limitation. Experimental results show that our method exhibits about 60% reduction in memory requirements during the training process. Furthermore, our method can reduce the overall training time beyond the existing algorithms. Compared to Checkmate, our approach achieves about 0.3–0.9% reduction in computation cost per iteration.

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MatrixMap: Programming Abstraction and Implementation of Matrix Computation for Big Data Applications

MatrixMap: Programming Abstraction and Implementation of Mat...

引用

International Conference on parallel and distributed Systems (ICPADS)

作者： Yaguang Huangfu Jiannong Cao Hongliang Lu Guanqing Liang Department of Computing The Hong Kong Polytechnic University Parallel and Distributed Processing Laboratory National University of Defense Technology

The computation core of many big data applications can be expressed as general matrix computations, including linear algebra operations and irregular matrix operations. However, existing parallel programming systems such as Spark do not have programming abstraction and efficient implementation for general matrix computations. In this paper, we present MatrixMap, a unified and efficient data-parallel system for general matrix computations. MatrixMap provides powerful yet simple abstraction, consisting of a distributed data structure called bulk key matrix and a computation interface defined by matrix patterns. Users can easily load data into bulk key matrices and program algorithms into parallel matrix patterns. MatrixMap outperforms current state-of-the-art systems by employing three key techniques: matrix patterns with lambda functions for irregular and linear algebra matrix operations, asynchronous computation pipeline with optimized data shuffling strategies for specific matrix patterns and in-memory data structure reusing data in iterations. Moreover, it can automatically handle the parallelization and distribute execution of programs on a large cluster. The experiment results show that MatrixMap is 12 times faster than Spark.

关键词： Data structures Programming Linear algebra Machine learning algorithms Sparks Sparse matrices Computational modeling

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Caste-centric agent-oriented programming

Caste-centric agent-oriented programming

引用

International Conference on Quality Software

作者： Ji Wang Rui Shen H. Zhu National Laboratory for Parallel and Distributed Processing Changsha China Department of Computing Oxford Brookes University Oxford UK

The paper presents a caste-centric approach to agent-oriented programming by introducing SLABSp language. The fundamental concepts of caste-centric methodology, caste and scenario, as well as environment descriptions, are available as language facilities in SLABSp in a coherent way. In SLABSp programming, agents are organized into castes to represent their structure and behavior characteristics, and their behaviors are defined by scenarios and rules in the context of their environment. The relations between agents and castes are bound at runtime, and the perceptions and interactions between agents are supported with scenarios and behavior rules. Two selected SLABSp programs are demonstrated to illustrate the programming style.

关键词： Programming profession Computer languages Object oriented modeling Runtime Multiagent systems Research and development Laboratories distributed processing Concurrent computing distributed computing

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Performance problems online detection in cloud computing systems via analyzing request execution paths

Performance problems online detection in cloud computing sys...

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International Conference on Dependable Systems and Networks Workshops (DSN-W)

作者： Haibo Mi Huaimin Wang Gang Yin Hua Cai Qi Zhou Tingtao Sun National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China Computing Platform Alibaba Cloud Computing Company Hangzhou China

It is quite a headache for developers to online detect performance problems in large-scale cloud computing systems. The behavior and the hidden connections among the huge amount of runtime request execution paths in cloud computing systems usually contain useful information for performance problem detection. In this paper, we propose an approach to rapidly diagnose the source of performance degradation in large-scale non-stop cloud computing systems. The approach first groups the user requests into categories with a fast clustering algorithm; then applies the principal components analysis to extract the primary methods; finally compares the normal and abnormal behaviors of the primary methods to localize the main cause of performance problems. We conduct extensive experiments over a real-world enterprise system providing services for the public. The results show that our approach can locate the prime causes of performance problems accurately and efficiently.

关键词： Cloud computing Principal component analysis Instruments Degradation Servers Data mining Accuracy

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Identifying faults in large-scale distributed systems by filtering noisy error logs

Identifying faults in large-scale distributed systems by fil...

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International Conference on Dependable Systems and Networks Workshops (DSN-W)

作者： Xiang Rao Huaimin Wang Dianxi Shi Zhenbang Chen Hua Cai Qi Zhou Tingtao Sun National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China Computing Platform Alibaba Cloud Computing Corporation Hangzhou China

Extracting fault features with the error logs of fault injection tests has been widely studied in the area of large scale distributed systems for decades. However, the process of extracting features is severely affected by a large amount of noisy logs. While the existing work tries to solve the problem by compressing logs in temporal and spatial views or removing the semantic redundancy between logs, they fail to consider the co-existence of other noisy faults that generate error logs instead of injected faults, for example, random hardware faults, unexpected bugs of softwares, system configuration faults or the error rank of a log severity. During a fault feature extraction process, those noisy faults generate error logs that are not related to a target fault, and will strongly mislead the resulted fault features. We call an error log that is not related to a target fault a noisy error log. To filter out noisy error logs, we present a similarity-based error log filtering method SBF, which consists of three integrated steps: (1) model error logs into time series and use haar wavelet transform to get the approximate time series; (2) divide the approximate time series into sub time series by valleys; (3) identify noisy error logs by comparing the similarity between the sub time series of target error logs and the template of noisy error logs. We apply our log filtering method in an enterprise cloud system and show its effectiveness. Compared with the existing work, we successfully filter out noisy error logs and increase the precision and the recall rate of fault feature extraction.

关键词： Time series analysis Noise measurement Feature extraction Wavelet transforms Computer crashes Complexity theory Approximation methods

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A Physics and Data-Driven Hybrid PINNs Intelligent computing Method for Nuclear Engineering Simulation 4

A Physics and Data-Driven Hybrid PINNs Intelligent Computing...

引用

4th International Conference on Electronic Information Engineering and Computer Science, EIECS 2024

作者： Xie, Yufei Wang, Wenlin Wu, Guohua Yu, Yang An, Ping Sun, Zibin Zhang, Haichuan Luo, Shengfeng Li, Yue School of Automation Wuhan University of Technology Wuhan China Sino-German College of Intelligent Manufacturing Shenzhen Technology University Shenzhen China Nuclear Power Institute of China Chengdu China National University of Defense Technology National Key Laboratory of Parallel and Distributed Computing Changsha China

ISBN: (纸本)9798331531409

In the field of nuclear energy, the Loss of Coolant Accident (LOCA) is recognized as one of the most severe types of nuclear reactor accidents, characterized by its complex physical processes and potentially catastrophic consequences. These challenges impose stringent requirements on safety analysis and emergency response. Accurate prediction and analysis of fluid behavior within pipelines under LOCA conditions are critical for evaluating accident outcomes and formulating response strategies. This paper introduces an innovative intelligent computing approach - a Physics-Informed Neural Networks (PINNs) model driven by both physical data and simulation data, specifically tailored for LOCA conditions. To address the challenges posed by multivariable and complex physical relationships, the six-equation two-fluid model is first simplified to represent the physical processes. Subsequently, a dual-driven PINNs network is developed, integrating both simulation data and physical constraints. The proposed model demonstrates a root mean square error (RMSE) of 0.02, a mean absolute error (MAE) of 0.044, and an R2 of 0.81 in predicting the outcomes under the six-equation model. © 2024 IEEE.

关键词： Nuclear energy

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