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International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS)

作者： A. Boukerche S.K. Das Center for Research in Parallel and Distributed Computing Center for Research in Parallel and Distributed Computing University of North Texas Denton TX USA

Load balancing is an important component in improving the efficiency of distributed systems because it distributes an even workload over all the processors. This paper considers the problem of load-balancing a conservative parallel simulation for execution on a multicomputer. The synchronization protocol makes use of Chandy-Misra (1979) null-messages. An earlier study conducted by Boukerche and Tropper (1994) showed that static load balancing for conservative parallel simulation is effective when the workload can be sufficiently well characterized beforehand. In this paper, we present a dynamic load balancing algorithm which assumes no compile-time knowledge about the workload parameters. It is based upon a process migration mechanism and the notion of CPU-queue length, which indicates the workload at each processor. We discuss the algorithm and its implementation, and report on the performance results of a simulation of FCFS (first-come, first-served) queueing network models on an Intel Paragon A4.

关键词： Load management Heuristic algorithms Computational modeling distributed computing Concurrent computing Protocols Performance gain Partitioning algorithms Computer simulation Constraint optimization

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PDRL-CM: An efficient cooperative caching management method for vehicular networks based on deep reinforcement learning

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Ad Hoc Networks 2025年 176卷

作者： Ou, Pingjie Chen, Ningjiang Yang, Long School of Computer and Electronic Information Guangxi University Nanning Guangxi530004 China Key Laboratory of Parallel Distributed and Intelligent Computing Education Department of Guangxi Zhuang Autonomous Region Nanning Guangxi530004 China The Guangxi Intelligent Digital Services Research Center of Engineering Technology Nanning Guangxi530004 China

In vehicular networks, onboard devices face the challenge of limited storage, and computational resources constrain their processing and storage capabilities. This limitation is particularly significant for applications that require complex computations and real-time responses. Additionally, limited storage capacity reduces the range of cacheable data, which can impact the immediate availability of data and the continuity of services. Therefore, improving cache utilization and meeting vehicles’ real-time data demands pose significant challenges. Deep reinforcement learning can optimize the issues arising from agents’ continuously changing state and action spaces due to increasing request demands. However, training the network may encounter instability and convergence difficulties in dynamic and complex environments or situations with sparse rewards. In response to these issues, this paper proposes a Priority-based Deep Reinforcement Learning Collaborative Cache Management method (PDRL-CM). PDRL-CM first designs a lightweight cache admission strategy that leverages data's inherent and combined attributes. It then makes cache admission decisions Using Monte Carlo sampling and a max-value search strategy combined with a feedforward neural network. Secondly, the method considers minimizing system latency and reducing vehicle energy consumption as joint optimization problems. An improved deep reinforcement learning algorithm solves this problem and makes cache-sharding decisions. A prioritized experience replay mechanism is incorporated to adjust the network prediction model quickly and accelerate the convergence process. Experimental results indicate that, compared to existing DRL-based caching methods, PDRL-CM offers faster data processing efficiency and higher cache hit rates under varying vehicle density, storage capacity, and content volume conditions. © 2025

关键词： Cache memory

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KC-GenRe: A Knowledge-constrained Generative Re-ranking Method Based on Large Language Models for Knowledge Graph Completion 30

KC-GenRe: A Knowledge-constrained Generative Re-ranking Meth...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Wang, Yilin Hu, Minghao Huang, Zhen Li, Dongsheng Yang, Dong Lu, Xicheng Defense Innovation Institute Academy of Military Sciences China Information Research Center of Military Science China National Key Laboratory of Parallel and Distributed Computing China

ISBN: (纸本)9782493814104

The goal of knowledge graph completion (KGC) is to predict missing facts among entities. Previous methods for KGC re-ranking are mostly built on non-generative language models to obtain the probability of each candidate. Recently, generative large language models (LLMs) have shown outstanding performance on several tasks such as information extraction and dialog systems. Leveraging them for KGC re-ranking is beneficial for leveraging the extensive pre-trained knowledge and powerful generative capabilities. However, it may encounter new problems when accomplishing the task, namely mismatch, misordering and omission. To this end, we introduce KC-GenRe, a knowledge-constrained generative re-ranking method based on LLMs for KGC. To overcome the mismatch issue, we formulate the KGC re-ranking task as a candidate identifier sorting generation problem implemented by generative LLMs. To tackle the misordering issue, we develop a knowledge-guided interactive training method that enhances the identification and ranking of candidates. To address the omission issue, we design a knowledge-augmented constrained inference method that enables contextual prompting and controlled generation, so as to obtain valid rankings. Experimental results show that KG-GenRe achieves state-of-the-art performance on four datasets, with gains of up to 6.7% and 7.7% in the MRR and Hits@1 metric compared to previous methods, and 9.0% and 11.1% compared to that without re-ranking. Extensive analysis demonstrates the effectiveness of components in KG-GenRe. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Knowledge graph

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A 55 TFLOPS simulation of amyloid-forming peptides from yeast prion Sup35 with the special-purpose computer system MDGRAPE-3

A 55 TFLOPS simulation of amyloid-forming peptides from yeas...

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2006 ACM/IEEE Conference on Supercomputing, SC'06

作者： Narumi, Tetsu Ohno, Yousuke Okimoto, Noriaki Koishi, Takahiro Suenaga, Atsushi Futatsugi, Noriyuki Yanai, Ryoko Himeno, Ryutaro Fujikawa, Shigenori Taiji, Makoto Ikei, Mitsuru Intel K.K. High Performance Molecular Simulation Team Genomic Sciences Center Innovative Nanopatterning Laboratory Topochemical Design Laboratory Frontier Research System Advanced Center for Computing and Communication Software and Solutions Group Parallel and Distributed Solutions Group

ISBN: (纸本)0769527000

We have achieved a sustained performance of 55 TFLOPS for molecular dynamics simulations of the amyloid fibril formation of peptides from the yeast Sup35 in an aqueous solution. For performing the calculations, we used the MDGRAPE-3 system - -a special-purpose computer system for molecular dynamics simulations. Its nominal peak performance was 415 TFLOPS for Coulomb force calculations;this is the highest-ever performance reported for classical molecular dynamics simulations. Amyloid fibril formation is known to be related to the occurrence of severe diseases such as Alzheimer's, Parkinson's, and Creutzfeldt-Jakob diseases. The Sup35 protein is a "yeast prion protein," which forms mini-crystals due to aggregation;it forms an effective platform for studying the formation process of amyloid fibrils. In these simulations, we first elucidate that the amyloid-forming peptides GNNQQNY aggregate at a higher frequency than non-amyloid-forming peptides SQNGNQQRG;further, the GNNQQNY peptides tend to form parallel two-stranded -sheets that would grow into a cross- amyloid nucleus. The results are consistent with those obtained experimentally. Furthermore, we could observe an early elongation of the amyloid nucleus. This result is expected to contribute toward a deeper understanding of the amyloid growth mechanism. © 2006 IEEE.

关键词： Peptides

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Dynamic load balancing strategies for conservative parallel simulations 97

Dynamic load balancing strategies for conservative parallel ...

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Proceedings of the eleventh workshop on parallel and distributed simulation

作者： Azzedine Boukerche Sajal K. Das Center for Research in Parallel and Distributed Computing Department of Computer Sciences University of North of Texas Denton TX

ISBN: (纸本)9780818679650

This paper studies the problem of load balancing for conservative parallel simulations for execution on a multicomputer. The synchronization protocol makes use of Chandy-Misra null-messages. We propose a dynamic load balancing algorithm which assumes no compile time knowledge about the workload parameters. It is based upon a process migration mechanism, and the notion of CPU-queue length, which indicates the workload at each *** examine two variations for the algorithm which we refer to as centralized and multi-level hierarchical methods, in the context of queueing network simulation of a torus. The torus was chosen because it of its many cycles aid in the formation of deadlock making it a stress test for any conservative synchronization protocols. Our experiments indicate that our dynamic load balancing schemes significantly reduce the run time of an optimized version of Chandy-Misra null message approach, and decreases by 30-40\% the synchronization overhead when compared to the use of a static partitioning algorithm. Significantly, the results obtained also indicate that the multi-level scheme always outperforms both the centralized load balancing approach and the static partitioning algorithm.

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A structured channel borrowing scheme for dynamic load balancing in cellular networks

A structured channel borrowing scheme for dynamic load balan...

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International Conference on distributed computing Systems

作者： S.K. Das S.K. Sen R. Jayaram Center for Research in Parallel and Distributed Computing Department of Computer Sciences University of North Texas Denton TX USA

We propose an efficient dynamic load balancing scheme in cellular networks for managing a teletraffic hot spot in which channel demand exceeds a certain threshold. A hot spot, depicted as a stack of hexagonal 'ring' of cells, is classified as complete if all cells within it are hot. The rings containing only cold cells outside the hot spot are called 'peripheral rings'. Our load balancing scheme migrates channels through a structured borrowing mechanism from the cold cells within the 'rings' or 'peripheral rings' to the hot cells in the hot spot. For the more general case of an incomplete hot spot, a cold cell is further classified as cold safe, cold semi-safe or cold unsafe, and a demand graph is constructed from the channel demand of each hot cell from its adjacent cells in the next outer ring. The channel borrowing algorithm works on the demand graph in a bottom up fashion, satisfying the demands of the cells in each subsequent inner ring. Markov chain models are developed for a hot cell and detailed simulation experiments are conducted to evaluate the performance of our load balancing scheme. Comparison with an existing load balancing strategy under moderate and heavy teletraffic conditions, shows a performance improvement of 12% in terms of call blockade by our load balancing scheme.

关键词： Load management Intelligent networks Land mobile radio cellular systems Frequency distributed computing Base stations Computer networks Concurrent computing Electronic mail Computer network management

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A Multi-Dimensional Assessment Model and Its Application in E-learning Courses of Computer Science 20

A Multi-Dimensional Assessment Model and Its Application in ...

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21st Annual Conference of the Special Interest Group in Information Technology Education, SIGITE 2020

作者： Luo, Jiwen Lu, Feng Wang, Tao Key Lab. of Parallel and Distributed Computing College of Computer National University of Defense Technology Changsha China National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781450370455

Computer science is a practical discipline. It is always a great challenge to evaluate students' computer practice using computer-aided means for large scale students. We always need to address problems such as suspected plagiarism and deviation of the overall difficulty factor. In this paper, a multi-dimensional assessment model is designed for CS courses based on the detailed practice processing data in an E-learning system. The model comprehensively evaluates the students' learning process and results in three aspects of correctness, originality, and quality detection. Besides, the teacher can easily participate in the assessment according to their needs. The correctness is an essential requirement, and the originality is based on the clustering results of students' behaviors after clone detection to curb homework plagiarism. SonarQube is used to detect code quality and put forward higher requirements for codes. Manual participation intelligence has improved the flexibility and applicability of the model to a certain extent. We applied this model on the EduCoder online education platform and carried out a comprehensive analysis of 485 students in the parallel Programming Principles and Practice Class of Huazhong University of Science and Technology. Experiment results confirm the distinction, rationality, and fairness of the model in assessing student performance. It not only gives students a credible, comprehensive score in large-scale online practical programming courses but also gives teachers and students corresponding suggestions based on the evaluation results. Furthermore, the model can be extended to other online education platforms. © 2020 ACM.

关键词： Students

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On the complexity of learning with a small number of nodes

On the complexity of learning with a small number of nodes

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International Joint Conference on Neural Networks (IJCNN)

作者： I. Parberry Center for Research in Parallel and Distributed Computing Department of Computer Sciences University of North Texas Denton TX USA

It is shown that the loading problem for a six-node neural network with a node function set AC/sub 10/, i.e., the conjunction or disjunction of a subset of the inputs or their complements is NP complete. It can be deduced from this observation that the loading problem for a six-node analog neural network is NP hard. The loading problem for a four-node neural network with a node function set equal to AC/sub 10/ plus the three-input equality function is shown to be NP complete, and it is indicated how the required results can be derived in a similar fashion. Three loading problems are studied.< >

关键词： Neural networks Computer architecture distributed computing Computer networks Boolean functions Concurrent computing Page description languages Electronic mail

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Cost-optimal parallel algorithms for finitely inductive sequences

Cost-optimal parallel algorithms for finitely inductive sequ...

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Annual Hawaii International Conference on System Sciences (HICSS)

作者： S.K. Das P.S. Fisher H. Zhang Center for Research in Parallel and Distributed Computing Department of Computer Science University of North Texas Denton TX USA

Finitely inductive (FI) sequences are a class of sequences, finite or infinite, which are amenable to a certain mathematical representation which has direct significance to pattern recognition and string matching. The authors propose cost-optimal parallel algorithms for FI sequence processing. These algorithms include parallel factoring and following by bucket packing and by hashing on an exclusive-read and exclusive-write (EREW), parallel random access machine (PRAM) model. Each of the algorithms achieves cost-optimal speedup under certain conditions as detailed.< >

关键词： parallel algorithms Pattern recognition Pattern matching distributed computing Computer science Impedance matching Phase change random access memory Multiple signal classification Signal detection Motion detection

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Cost-optimal parallel algorithms for traversing trees

Cost-optimal parallel algorithms for traversing trees

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IEEE Southeastcon

作者： S.K. Das C.C.-Y. Chen Center of Research in Parallel and Distributed Computing Department of Computer Science University of North Texas Denton TX USA

The authors present cost-optimal parallel algorithms for depth-order (e.g., pre-, in-, and post-order) and level-order (e.g., breadth-first and breadth-depth) traversals of general trees with n nodes. Each of the algo... 详细信息

关键词： parallel algorithms Phase change random access memory Computer science Binary trees distributed computing Classification tree analysis Algorithm design and analysis

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