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International Symposium on parallel Architectures, Algorithms and Programming (PAAP)

作者： Yao Li Cheng Zhong Danyang Chen Jinxiong Zhang Mengxiao Yin Key Laboratory of Parallel School of Computer Electronics and Information Distributed Computing Technology in Guangxi Universities Guangxi University Nanning China

ISBN: (纸本)9781665496407

A large number of reads generated by the next generation sequencing platform will contain many repetitive subsequences. Effective localizing and identifying genomic regions containing repetitive subsequences will contribute to the subsequent genomic data analysis. To accelerate the alignment between large-scale short reads and reference genome with many repetitive subsequences, this paper develops a compact de Bruijn graph based short-read alignment algorithm on distributed parallel computing platform. The algorithm uses resilient distributed data sets (RDDS) to perform calculations in memory, and executes the broadcast method to distribute short reads and reference genome to the computing nodes to reduce the data communication time on the cluster system, and the number of RDD partitions is set to optimize the performance of parallel aligning algorithm. Experimental results on real datasets show that compared with the compact de Bruijn graph based sequential short-read alignment algorithm, our implemented distributed parallel alignment algorithm achieves good acceleration on the premise of obtaining the same correct alignment percentage as a whole, and compared with existing distributed parallel alignment algorithms, the implemented parallel algorithm can more quickly complete the alignment between large-scale short reads and reference genome with highly repetitive subsequences.

关键词： Sequential analysis Genomics Clustering algorithms distributed databases Programming Partitioning algorithms parallel architectures

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A multi-layered emulation platform to verify the effectiveness of consistency control approaches about message ordering

A multi-layered emulation platform to verify the effectivene...

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IEEE International Conference on Communication Software and Networks

作者： Zhou, Hangjun Fu, Sha Department of Information Management Hunan University of Finance and Economics Chang Sha Hu Nan China Key Laboratory of Science and Technology for National Defence of Parallel and Distributed Processing School of Computer Science National University of Defense Technology Chang Sha Hu Nan China

ISBN: (纸本)9781612844855

It is an important issue to preserve the consistent delivering order of messages at each site in distributed Virtual Environments(DVEs). Currently, the violations of message delivery order are inclined to happen in the large-scale and frequently interactive DVEs running on Wide Area Network(WAN). The inconsistent anomalies are characterized as unpredictable, unrepeatable and uncontrollable, which results in the severe problem for the development of the consistency control approaches. Meanwhile, it is also highly expensive to directly verify the proposed approaches on WAN. Therefore, in this paper, we design and establish an original multi-layered emulation platform in LAN, which can emulate the network latency of WAN and repeat the scenarios of violations. On the platform, the designers of consistency approaches don't have to spend efforts to realize the fundamental functions of the verification, but could pay more attention to the development and optimization of the control algorithms, which is very beneficial for the improvement of message ordering approaches. © 2011 IEEE.

关键词： Wide area networks

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AutoMal: Automatic clustering and signature generation for malwares based on the network flow

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Security and Communication Networks 2015年第10期8卷 1845-1854页

作者： Hao, Sun Wang, Wen Lu, Huabiao Ren, Peige School of Computer National University of Defense Technology Changsha China National Key Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China

The volume of malwares is growing at an exponential speed nowadays. This huge growth makes it extremely hard to analyse malware manually. Most existing signatures extracting methods are based on string signatures, and string matching is not accurate and time consuming. Therefore, this paper presents AutoMal, a system for automatically extracting signatures from large-scale malwares. Firstly, the system proposes to represent the network flows by using feature hashing, which can dramatically reduce the high-dimensional feature spaces that are general in malware analysis. Then, we design a clustering and median filtering method to classify the malware vectors into different types. Finally, it introduces the signature generation algorithm based on Bayesian method. The system can extract both the byte signature and the hash signature of malwares from its network flow with low false positive and zero false negative. Our evaluation shows that AutoMal can generate strongly noise-resisted signatures that exactly depict the characteristics of malware. © 2014 John Wiley & Sons, Ltd.

关键词： Malware

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Research of Context Situation Awareness Technology

Research of Context Situation Awareness Technology

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IEEE International Symposium on Object/Component/Service-Oriented Real-Time distributed computing Workshops (ISORCW)

作者： Dianxi Shi Zhendong Wu Bo Ding Huining Yan National Key Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha China

Context situation, which means a snapshot of the status of the real world, is formed by integrating a large amount of contexts collected from various resources. How to get the context situation and use the situation to provide better services is a challenging issue. In this paper, we focused on this challenge on the basis of the mobile cloud computing architecture. An abstract model is proposed in this paper to uniformly collect the context and send them to cloud. A rule-based large-scale context aggregation algorithm is also proposed which utilizes the MapReduce computing paradigm. Finally, a large-scale context management framework based on the abstract model and the context aggregation algorithm is proposed, and a real-time traffic demo is implemented to verify the validity of the framework.

关键词： Context Mobile handsets Real time systems Sensors Servers Mobile communication Context modeling

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A prompt-based approach to adversarial example generation and robustness enhancement

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Frontiers of Computer Science 2024年第4期18卷 85-96页

作者： Yuting YANG Pei HUANG Juan CAO Jintao LI Yun LIN Feifei MA Key Lab of Intelligent Information Processing of Chinese Academy of Sciences(CAS) Institute of Computing TechnologyCASBeijing 100190China School of Computer Science and Technology University of Chinese Academy of SciencesBeijing 100049China Department of Computer Science Stanford UniversityCA 94305USA School of Computing National University of SingaporeSingapore 119077Singapore Laboratory of Parallel Software and Computational Science Institute of SoftwareChinese Academy of SciencesBeijing 100190China

Recent years have seen the wide application of natural language processing(NLP)models in crucial areas such as finance,medical treatment,and news media,raising concerns about the model robustness and *** find that prompt paradigm can probe special robust defects of pre-trained language *** prompt texts are first constructed for inputs and a pre-trained language model can generate adversarial examples for victim models via *** results show that prompt paradigm can efficiently generate more diverse adversarial examples besides synonym ***,we propose a novel robust training approach based on prompt paradigm which incorporates prompt texts as the alternatives to adversarial examples and enhances robustness under a lightweight minimax-style optimization *** on three real-world tasks and two deep neural models show that our approach can significantly improve the robustness of models to resist adversarial attacks.

关键词： robustness adversarial example prompt learning pre-trained language model

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ACCURATE AND EFFICIENT FINE-TUNING OF QUANTIZED LARGE LANGUAGE MODELS THROUGH OPTIMAL BALANCE

arXiv

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arXiv 2024年

作者： Shen, Ao Wang, Qiang Lai, Zhiquan Li, Xionglve Li, Dongsheng National Key Laboratory of Parallel and Distributed Computing National University of Defense Technology Hunan Changsha410073 China College of computer National University of Defense Technology Hunan Changsha410073 China

Large Language Models (LLMs) have demonstrated impressive performance across various domains. However, the enormous number of model parameters makes fine-tuning challenging, significantly limiting their application and deployment. Existing solutions combine parameter quantization with Low-Rank Adaptation (LoRA), greatly reducing memory usage but resulting in noticeable performance degradation. In this paper, we identify an imbalance in fine-tuning quantized pre-trained models: overly complex adapter inputs and outputs versus low effective trainability of the adaptation. We propose Quantized LLMs with Balanced-rank Adaptation (Q-BaRA), which simplifies the adapter inputs and outputs while increasing the adapter’s rank to achieve a more suitable balance for finetuning quantized LLMs. Additionally, for scenarios where fine-tuned LLMs need to be deployed as low-precision inference models, we introduce Quantization-Aware Fine-tuning with Higher Rank Adaptation (QA-HiRA), which simplifies the adapter inputs and outputs to align with the pre-trained model’s block-wise quantization while employing a single matrix to achieve a higher rank. Both Q-BaRA and QA-HiRA are easily implemented and offer the following optimizations: (i) Q-BaRA consistently achieves the highest accuracy compared to baselines and other variants, requiring the same number of trainable parameters and computational effort;(ii) QA-HiRA naturally merges adapter parameters into the block-wise quantized model after fine-tuning, achieving the highest accuracy compared to other methods. We apply our Q-BaRA and QA-HiRA to the LLaMA and LLaMA2 model families and validate their effectiveness across different fine-tuning datasets and downstream scenarios. Copyright © 2024, The Authors. All rights reserved.

关键词： Digital elevation model

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Predicting Programming Behavior in OSS Communities: A Case Study of NLP-based Approach

Predicting Programming Behavior in OSS Communities: A Case S...

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Artificial Intelligence and Computer Engineering (ICAICE), International Conference on

作者： Manyan Huo Yue Yu Zhixing Li Junsheng Chang Key Lab. of Parallel and Distributed Computing Lab. College of Computer National University of Defence Technology ChangSha China

ISBN: (数字)9781728191461

ISBN: (纸本)9781728191478

Prediction of developers' programming behaviors is an effective way to improve their development efficiency and optimize the organization of project modules and files. However, little research exists investigating on this direction. In order to address this knowledge gap, we proposed a NLP-based approach to predict the programming behaviors in OSS (Open Source Software) communities. The proposed approach i) embeds the historical programming behavior data of a project into a multi-dimensional vector space to capture the potential laws in the data, ii) forms an eigenvector matrix reflecting the semantic relationship of the development behavior data, and iii) predicts the next programming behavior of a specific developer based on the eigenvector matrix. Our experiments on five OSS projects show that the prediction accuracy rate of the proposed prediction approach can reach up to about 50%, indicating that it can summarize the development behavior data law and effectively predict the programming behavior of developers. Our work can provide valuable assistance for developers' programming and projects' maintenance in practice.

关键词： Training Semantics Programming Predictive models Prediction algorithms Data models Context modeling

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An Interface Theory Based Approach to Verification of Web Services

An Interface Theory Based Approach to Verification of Web Se...

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IEEE Annual International Computer Software and Applications Conference (COMPSAC)

作者： Zhenbang Chen Ji Wang Wei Dong Zhichang Qi W.l. Yeung National Laboratory for Parallel and Distributed Processing Changsha China Department of Computing and Decision Sciences Lingnan University Hong Kong China

The verification of Web services becomes a challenge in software verification. This paper presents a framework for verification of Web service interfaces at various abstraction levels. Its foundation is the interface theory for Web services, in which transaction features are incorporated. Within the framework, one may check non mutual invocation, compatibility and refinement of Web services at signature, conversation and protocol levels. At protocol level, we present a model checking approach to verifying the protocol properties in action set computation tree logic (ASCTL). The paper also discusses the integration of our framework into the Web service development

关键词： Web services Protocols Laboratories distributed processing Supply chain management Automata distributed computing Research and development Computer applications Computer interfaces

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Towards MLOps: A Case Study of ML Pipeline Platform

Towards MLOps: A Case Study of ML Pipeline Platform

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Artificial Intelligence and Computer Engineering (ICAICE), International Conference on

作者： Yue Zhou Yue Yu Bo Ding Key Lab. of Parallel and Distributed Computing Lab. College of Computer National University of Defence Technology ChangSha China

ISBN: (数字)9781728191461

ISBN: (纸本)9781728191478

The development and deployment of machine learning (ML) applications differ significantly from traditional applications in many ways, which have led to an increasing need for efficient and reliable production of ML applications and supported infrastructures. Though platforms such as TensorFlow Extended (TFX), ModelOps, and Kubeflow have provided end-to-end lifecycle management for ML applications by orchestrating its phases into multistep ML pipelines, their performance is still uncertain. To address this, we built a functional ML platform with DevOps capability from existing continuous integration (CI) or continuous delivery (CD) tools and Kubeflow, constructed and ran ML pipelines to train models with different layers and hyperparameters while time and computing resources consumed were recorded. On this basis, we analyzed the time and resource consumption of each step in the ML pipeline, explored the consumption concerning the ML platform and computational models, and proposed potential performance bottlenecks such as GPU utilization. Our work provides a valuable reference for ML pipeline platform construction in practice.

关键词： Training Computational modeling Pipelines Graphics processing units Tools Data models Task analysis

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Device View Redundancy: an adaptive low-overhead fault tolerance mechanism for many-core system

Device View Redundancy: an adaptive low-overhead fault toler...

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International Workshop on Intelligent Communication and Social Networks

作者： Wentao Jia Chunyuan Zhang Jian Fu National Key Laboratory of Parallel and Distributed Processing College of Computer National University of Defense Technology Institute for Informatics University of Amsterdam

ISBN: (纸本)9781479909735

Continued increasing of fault rate in integrate circuit makes processors more susceptible to errors, especially many-core processor. Meanwhile, most systems or applications do not need full fault coverage, which has excessive overhead. So on-demand fault tolerance is desired for these applications. In this paper, we propose an adaptive low-overhead fault tolerance mechanism for many-core system, called Device View Redundancy (DVR). It treats fault tolerance as a device that can be configured and used by application when high reliability is needed. Nevertheless, DVR exploits the idle resources for low-overhead fault tolerance, which is based on the observation that the utilization of many-core system is low due to lack of parallelism in application. Finally, the experiment shows that the performance overhead of DVR is reduced by 16% to 98% compared with full Dual Modular Redundancy (DMR).

关键词： On-demand redundancy Idle resource exploitation Dynamic coupling Low-overhead Many core system

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