检索结果-内蒙古大学图书馆

IEEE International Conference on computer Design: VLSI in computers and Processors, (ICCD)

作者： Wenjie Qi Zhipeng Tan Ziyue Zhang Jing Zhang Chao Yu Ying Yuan Shikai Tan Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System Engineering Research Center of Data Storage Systems and Technology Ministry of Education of China School of Computer Science & Technology Huazhong University of Science & Technology Guangdong Oppo Mobile Telecommunications Corp. Ltd

Emerging Zoned Namespace (ZNS) SSDs provide hosts with fine-grained, performance-predictable storage management. The ZNS SSD divides its address space into zones, and each zone must be written sequentially and cannot be overwritten. However, the write constraint results in frequent small modifications of file metadata to record the latest logical block addresses of the updated data blocks, increasing the overhead of fsync() system call. We comprehensively analyze the metadata overhead of fsync on a real ZNS SSD and find that (1) the update size of most metadata blocks (e.g., tens of bytes) is far less than the IO unit of the zone (e.g., 4 KiB), and frequent fsyncs cause severe metadata write amplification; (2) metadata block IOs significantly increase the fsync latency, decreasing the throughput of *** reduce the metadata overhead of fsync, we build the byte-loggable zone based on the persistent write cache of the opened zone, a novel extension of ZNS, which can be appended at byte granularity instead of block. Based on the byte-loggable zone, we present BlzFS, a high-performance and crash-consistent file system for ZNS SSD. Firstly, BlzFS maintains the update ranges of the metadata block by the update bitmap. Secondly, BlzFS ensures the persistence and consistency of metadata by logging the partial updates of metadata blocks to the device’s byte-loggable zone. Finally, BlzFS restores metadata consistency by replaying the metadata update log and scanning the list of recent allocated metadata blocks. In the evaluation, BlzFS shows a 33.5%∼96.1% reduction in metadata write traffic and a 1.37×∼1.91× throughput improvement compared with the original ZNS storage system.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Charging Dynamic Sensors through Online Learning

Charging Dynamic Sensors through Online Learning

引用

IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： Yu Sun Chi Lin Wei Yang Jiankang Ren Lei Wang Guowei Wu Qiang Zhang School of Software Technology Dalian University of Technology Dalian China The State Key Laboratory of Integrated Services Networks Xidian University Xi’an China Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province Dalian China School of Computer Science and Technology Dalian University of Technology Dalian China

As a novel solution for IoT applications, wireless rechargeable sensor networks (WRSNs) have achieved widespread deployment in recent years. Existing WRSN scheduling methods have focused extensively on maximizing the network charging utility in the fixed node case. However, when sensor nodes are deployed in dynamic environments (e.g., maritime environments) where sensors move randomly over time, existing approaches are likely to incur significant performance loss or even fail to execute normally. In this work, we focus on serving dynamic nodes whose locations vary randomly and formalize the dynamic WRSN charging utility maximization problem (termed MATA problem). Through discretizing candidate charging locations and modeling the dynamic charging process, we propose a near-optimal algorithm for maximizing charging utility. Moreover, we point out the long-short-term conflict of dynamic sensors that their location distributions in the short-term usually deviate from the long-term expectations. To tackle this issue, we further design an online learning algorithm based on the combinatorial multi-armed bandit (CMAB) model. It iteratively adjusts the charging strategy and adapts well to nodes’ short-term location deviations. Extensive experiments and simulations demonstrate that the proposed scheme can effectively charge dynamic sensors and achieve a higher charging utility compared to baseline algorithms in both long-term and short-term.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Dynamic cluster strategy for hierarchical rollback-recovery protocols in MPI HPC applications

Dynamic cluster strategy for hierarchical rollback-recovery ...

引用

作者： Liao, Xiaofei Zheng, Long Zhang, Binsheng Zhang, Yu Jin, Hai Shi, Xuanhua Lin, Yi Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China College of Computer Science and Technology Civil Aviation University of China Tianjin300300 China

Fault tolerance in parallel computing becomes increasingly important with a significant rise in high-performance computing systems. Coordinated checkpointing and message logging protocols are commonly used fault tolerance mechanisms for message-passing applications. However, these mechanisms are insufficient because of their severe drawbacks. Hierarchical rollback-recovery protocols, combining coordinated checkpointing with message logging, are a better solution. However, such protocols may not obtain the appropriate efficiency because the communication pattern in different stages of applications may vary at runtime. In an effort to improve the efficiency of hierarchical rollback-recovery protocols, we propose a dynamic cluster strategy to adapt to the runtime variation of communication pattern by using a prediction scheme. Finally, the efficiency and scalability of the dynamic cluster strategy are evaluated using 2 static process partition algorithms on the High-Performance Linpack benchmark. © 2017 John Wiley & Sons, Ltd.

关键词： Message passing

来源：评论

学校读者我要写书评

暂无评论

Improving Deep Assertion Generation via Fine-Tuning Retrieval-Augmented Pre-trained Language Models

arXiv

引用

arXiv 2025年

作者： Zhang, Quanjun Fang, Chunrong Zheng, Yi Zhang, Yaxin Zhao, Yuan Huang, Rubing Zhou, Jianyi Yang, Yun Zheng, Tao Chen, Zhenyu Department of Computing Technologies Swinburne University of Technology Melbourne Australia State Key Laboratory for Novel Software Technology Nanjing University Jiangsu Nanjing China School of Computer Science and Engineering Macau University of Science and Technology Jiangsu Nanjing China Huawei Cloud Computing Technologies Co. Ltd. Beijing China Shenzhen Research Institute of Nanjing University Guangdong Shenzhen China

Unit testing validates the correctness of the units of the software system under test and serves as the cornerstone in improving software quality and reliability. To reduce manual efforts in writing unit tests, some techniques have been proposed to generate test assertions automatically, including deep learning (DL)-based, retrieval-based, and integration-based ones. Among them, recent integration-based approaches inherit from both DL-based and retrieval-based approaches and are considered state-of-the-art. Despite being promising, such integration-based approaches suffer from inherent limitations, such as retrieving assertions with lexical matching while ignoring meaningful code semantics, and generating assertions with a limited training corpus. In this paper, we propose a novel Retrieval-Augmented Deep Assertion Generation approach, namely RetriGen, based on a hybrid assertion retriever and a pre-trained language model (PLM)-based assertion generator. Given a focal-test, RetriGen first builds a hybrid assertion retriever to search for the most relevant test-assert pair from external codebases. The retrieval process takes both lexical similarity and semantical similarity into account via a token-based and an embedding-based retriever, respectively. RetriGen then treats assertion generation as a sequence-to-sequence task and designs a PLM-based assertion generator to predict a correct assertion with historical test-assert pairs and the retrieved external assertion. Although our concept is general and can be adapted to various off-the-shelf encoder-decoder PLMs, we implement RetriGen to facilitate assertion generation based on the recent CodeT5 model. We conduct extensive experiments to evaluate RetriGen against six state-of-the-art approaches across two large-scale datasets and two metrics. The experimental results demonstrate that RetriGen achieves 57.66% and 73.24% in terms of accuracy and CodeBLEU, outperforming all baselines with an average improvement of 50.66

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Adaptive Gaussian Regularization Constrained Sparse Subspace Clustering for Image Segmentation

Adaptive Gaussian Regularization Constrained Sparse Subspace...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Sensen Song Dayong Ren Zhenhong Jia Fei Shi School of Computer Science and Technology Xinjiang University Urumqi China Key Laboratory of Signal Detection and Processing Xinjiang Uygur Autonomous Region Urumqi China College of Mathematics and System Science Xinjiang University Urumqi China National Key Laboratory for Novel Software Technology Nanjing University Nanjing China

Sparse Subspace Clustering (SSC) is integral to image processing, drawing from spectral clustering foundations. However, prevalent methods, relying on an l 1 -norm constraint, fail to capture nuanced inter-region correlations, affecting segmentation efficacy. To remedy this, we introduce an Adaptive Gaussian Regularization Constrained SSC for enhanced image segmentation. This method begins with superpixel preprocessing to enrich local information. Given the Gaussian nature of the SSC’s sparse coefficient matrix, a Gaussian probability density function is infused as a regularization term, reinforcing regional image ties and facilitating similarity matrix creation. Using spectral clustering, we then define superpixel clusters leading to the final segmentation. When tested against the BSDS500 and SBD datasets and other leading algorithms, our model showcases marked improvements in natural image segmentation.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Tracking Objects and Activities with Attention for Temporal Sentence Grounding

Tracking Objects and Activities with Attention for Temporal ...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Zeyu Xiong Daizong Liu Pan Zhou Jiahao Zhu Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wangxuan Institute of Computer Technology Peking University

Temporal sentence grounding (TSG) aims to localize the temporal segment which is semantically aligned with a natural language query in an untrimmed video. Most existing methods extract frame-grained features or object-grained features by 3D ConvNet or detection network under a conventional TSG framework, failing to capture the subtle differences between frames or to model the spatio-temporal behavior of core persons/objects. In this paper, we introduce a new perspective to address the TSG task by tracking pivotal objects and activities to learn more fine-grained spatio-temporal behaviors. Specifically, we propose a novel Temporal Sentence Tracking Network (TSTNet), which contains (A) a Cross-modal Targets Generator to generate multi-modal templates and search space, filtering objects and activities, and (B) a Temporal Sentence Tracker to track multi-modal targets for modeling the targets’ behavior and to predict query-related segment. Extensive experiments and comparisons with state-of-the-arts are conducted on challenging benchmarks: Charades-STA and TACoS. And our TSTNet achieves the leading performance with a considerable real-time speed.

关键词： Solid modeling Target tracking Three-dimensional displays Grounding Benchmark testing Signal processing Feature extraction

来源：评论

学校读者我要写书评

暂无评论

BED: A Block-Level Deduplication-Based Container Deployment Framework 15th

BED: A Block-Level Deduplication-Based Container Deployment ...

引用

15th International Conference on Green, Pervasive, and Cloud computing, GPC 2020

作者： Zhang, Shiqiang Wu, Song Fan, Hao Zou, Deqing Jin, Hai 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 Scinece and Technology Wuhan430074 China

ISBN: (纸本)9783030642426

Container technology has gained great popularity in cloud environment since containers provide near-native performance and are lighter and less expensive than traditional virtual machines. However, starting up a non-local container, whose image is unavailable locally, is time-consuming. The reason is that pulling an image from a remote registry requires a long time. In this paper, we experimentally find that a lot of redundant data exists among image layers when we pull images from the registry. This redundant data causes additional pull time and makes the startup of a non-local container slower. To minimize the amount of pulled data while providing intact images, we propose a container deployment framework, BED, based on block-level deduplication. To be specific, BED stores an image layer as numerous data blocks and a fingerprint list which is generated based on these data blocks. When BED needs to pull an image, it pulls the fingerprint lists of the image, deduplicates these fingerprint lists, and pulls the data blocks non-existing locally from the registry. Based on the local and pulled blocks, BED reconstructs the image layers for a container. Experiments show that compared with original Docker, BED reduces the time of pulling images by 35% on average and saves about 48% data transmission in the network. © 2020, Springer Nature Switzerland AG.

关键词： Containers

来源：评论

学校读者我要写书评

暂无评论

Privacy-Preserving and Verifiable Outsourcing Inference Against Malicious Servers

Privacy-Preserving and Verifiable Outsourcing Inference Agai...

引用

IEEE Conference on Global Communications (GLOBECOM)

作者： Yiyao Liu Hongwei Li Meng Hao Xilin Zhang Guiqiang Hu School of Computer Science and Engineering University of Electronic Science and Technology of China State Key Laboratory of Integrated Services Networks Xidian University School of Artificial Intelligence Chongqing University of Arts and Sciences

Outsourcing inference enables users to outsource neural network inference tasks to a service provider (e.g., a remote server). This paradigm has brought enormous convenience and effectively solved the resource-limited issues of users, especially for mobile devices. However, it still suffers from two challenges: (1) The user's input data and inference results contain a large amount of private information, which should not be disclosed. (2) The server in this setting may be malicious and hence violate the inference procedure. For example, the server may use a low-quality model to reduce costs or return wrong inference results. While several privacy-preserving inference works have been proposed, they cannot solve the above two problems at the same time. In this work, we propose PPVI, a secure and verifiable outsourcing inference scheme against malicious service providers. PPVI designs a hybrid check technique for inference integrity verification and employs leveled homomorphic encryption to protect users' privacy. These ingredients together make it possible to protect users' privacy and verify the inference correctness in outsourcing inference simultaneously. Extensive experiment results demonstrate our scheme has an excellent performance in terms of verification accuracy and communication and computational overhead.

关键词：

来源：评论

学校读者我要写书评

暂无评论

MFGB: Molecular Properties Prediction leveraging Self-supervised Morgan Fingerprint Representation Learning

MFGB: Molecular Properties Prediction leveraging Self-superv...

引用

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Shuyan Fang Yu Liu Song Liu School of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Provincial Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan University of Science and Technology Wuhan China Hubei Provincial Key Laboratory of Occupational Hazard Identification and Control Hubei Province Wuhan University of Science and Technology Wuhan China

Simple molecular graphs or molecular line notations are insufficient for molecular representation learning models that automatically learn molecule representations to acquire deep semantic features about chemistry. Therefore, we proposed the Morgan Fingerprint Graph, a novel molecular graph model constructed with the nodes of the Morgan Fingerprint Identifier, whose nodes incorporate various properties of the atom neighborhood. Based on our Morgan Fingerprint Graph, we trained a BERT-based molecular representation model MFGB which employs a local rather than global attention module to adapt the model to the Morgan Fingerprint Graph. The attention module of MFGB regulates the exchange of information in the attention layer based on the connection information of the atoms in the molecules. To verify the effectiveness of MFGB, we selected several mainstream datasets for evaluation. The results demonstrated that our method improve the performance of molecular properties prediction. In addition, we analyzed MFGB from both the over-smoothing and the attention perspectives. The analysis indicates that the node vector representations learned from the Morgan Fingerprint Graph are generally less smoothing, and the attention distributions of MFGB match the partial charge density distribution of the molecules.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Design of multi-channel synchronization signal acquisition method based on FPGA

Design of multi-channel synchronization signal acquisition m...

引用

Chinese Control and Decision Conference, CCDC

作者： Feiqing Zhang Dongji Li Zhenyu Yin Guangyuan Xu Shuo Li Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Liaoning Key Laboratory of Domestic Industrial Control Platform Technology on Basic Hardware & Software Shenyang China School of Computer Science and Technology Shenyang University of Chemical Technology Shenyang China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

In the field of aerospace, engines play a vital role, and rolling bearings, as the core components within them, have a significant impact on the production and operation of the entire equipment system. Therefore, real-time monitoring of the engine to ensure the safe operation of the equipment is indispensable. Therefore, this paper designs and implements a multi-channel synchronous acquisition card system based on FPGA platform to realize real-time acquisition of engine vibration signals, and then analyzes its running state and makes accurate judgments. Aiming at the problems of slow information interaction speed and high bit error rate between FPGA and host computer, we design a message interaction optimization method based on UART, which successfully improved the speed and accuracy of data transmission. At the same time, in order to solve the problem of complex and difficult management of system parameters, we design a RAM based addressing storage method, which can effectively realize the long-term storage of parameters and ensure the stability of data. And the method adopts modularization and parametric design strategy, so it has high portability. The simulation results show that the signal-to-noise ratio of the method can reach 95dB and the power consumption is only 0.26W, which meets the requirements of vibration signal acquisition and power consumption. These characteristics make the system have high engineering application value in the field of aerospace engine monitoring.

关键词： Vibrations Power demand Accuracy Simulation Real-time systems Stability analysis Synchronization

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：