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Resource abstraction and data placement for distributed hybrid memory pool

Frontiers of Computer Science 2021年第3期15卷 47-57页

作者： Tingting CHEN Haikun LIU Xiaofei LIAO Hai JIN National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab/Gluster and Grid Computing LabSchool of Gomputing Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China

Emerging byte-addressable non-volatile memory(NVM)technologies offer higher density and lower cost than DRAM,at the expense of lower performance and limited write *** have been many studies on hybrid NVM/DRAM memory management in a single physical ***,it is still an open problem on how to manage hybrid memories efficiently in a distributed *** paper proposes Alloy,a memory resource abstraction and data placement strategy for an RDMA-enabled distributed hybrid memory pool(DHMP).Alloy provides simple APIs for applications to utilize DRAM or NVM resource in the DHMP,without being aware of the hardware details of the *** propose a hotness-aware data placement scheme,which combines hot data migration,data replication and write merging together to improve application performance and reduce the cost of *** evaluate Alloy with several micro-benchmark workloads and public benchmark *** results show that Alloy can significantly reduce the DRAM usage in the DHMP by up to 95%,while reducing the total memory access time by up to 57%compared with the state-of-the-art approaches.

关键词： load balance distributed hybrid memory clouds

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UCat: heterogeneous memory management for unikernels

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Frontiers of Computer Science 2023年第1期17卷 51-61页

作者： Chong TIAN Haikun LIU Xiaofei LIAO Hai JIN National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab/Cluster and Grid Computing LabSchool of Computing Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China

Unikernels provide an efficient and lightweight way to deploy cloud computing services in application-specialized and single-address-space virtual machines (VMs). They can efficiently deploy hundreds of unikernel-based VMs in a single physical server. In such a cloud computing platform, main memory is the primary bottleneck resource for high-density application deployment. Recently, non-volatile memory (NVM) technologies has become increasingly popular in cloud data centers because they can offer extremely large memory capacity at a low expense. However, there still remain many challenges to utilize NVMs for unikernel-based VMs, such as the difficulty of heterogeneous memory allocation and high performance overhead of address *** this paper, we present UCat, a heterogeneous memory management mechanism that support multi-grained memory allocation for unikernels. We propose front-end/back-end cooperative address space mapping to expose the host memory heterogeneity to unikernels. UCat exploits large pages to reduce the cost of two-layer address translation in virtualization environments, and leverages slab allocation to reduce memory waste due to internal memory fragmentation. We implement UCat based on a popular unikernel--OSv and conduct extensive experiments to evaluate its efficiency. Experimental results show that UCat can reduce the memory consumption of unikernels by 50% and TLB miss rate by 41%, and improve the throughput of real-world benchmarks such as memslap and YCSB by up to 18.5% and 14.8%, respectively.

关键词： unikernel virtualization non-volatile memory heterogeneous memory large page slab allocation

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Precise control of page cache for containers

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Frontiers of Computer Science 2024年第2期18卷 17-30页

作者： Kun WANG Song WU Shengbang LI Zhuo HUANG Hao FAN Chen YU Hai JIN National Engineering Research Center for Big Data Technology and System Services Computing Technology and System LabCluster and Grid Computing Lab School of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China

Container-based virtualization isbecoming increasingly popular in cloud computing due to its efficiency and *** isolation is a fundamental property of *** works have indicated weak resource isolation could cause significant performance degradation for containerized applications and enhanced resource ***,current studies have almost not discussed the isolation problems of page cache which is a key resource for *** leverage memory cgroup to control page cache ***,existing policy introduces two major problems in a container-based ***,containers can utilize more memory than limited by their cgroup,effectively breaking memory ***,the Os kernel has to evict page cache to make space for newly-arrived memory requests,slowing down containerized *** paper performs an empirical study of these problems and demonstrates the performance impacts on containerized *** we propose pCache(precise control of page cache)to address the problems by dividing page cache into private and shared and controlling both kinds of page cache separately and *** do so,pCache leverages two new technologies:fair account(f-account)and evict on demand(EoD).F-account splits the shared page cache charging based on per-container share to prevent containers from using memory for free,enhancing memory *** EoD reduces unnecessary page cache evictions to avoid the performance *** evaluation results demonstrate that our system can effectively enhance memory isolation for containers and achieve substantial performance improvement over the original page cache management policy.

关键词： page cache memory cgroup container isolation cloud computing

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ReCSA:a dedicated sort accelerator using ReRAM-based content addressable memory

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Frontiers of Computer Science 2023年第2期17卷 1-13页

作者： Huize LI Hai JIN Long ZHENG Yu HUANG Xiaofei LIAO National Engineering Research Center for Big Data Technology and System Services Computing Technology and System LabClusters and Grid Computing LabSchool of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China

With the increasing amount of data,there is an urgent need for efficient sorting algorithms to process large data *** sorting algorithms have attracted much attention because they can take advantage of different hardware's *** the traditional hardware sort accelerators suffer“memory wall”problems since their multiple rounds of data transmission between the memory and the *** this paper,we utilize the in-situ processing ability of the ReRAM crossbar to design a new ReCAM array that can process the matrix-vector multiplication operation and the vector-scalar comparison in the same array *** this designed ReCAM array,we present ReCSA,which is the first dedicated ReCAM-based sort *** hardware designs,we also develop algorithms to maximize memory utilization and minimize memory exchanges to improve sorting *** sorting algorithm in ReCSA can process various data types,such as integer,float,double,and *** also present experiments to evaluate the performance and energy efficiency against the state-of-the-art sort *** experimental results show that ReCSA has 90.92×,46.13×,27.38×,84.57×,and 3.36×speedups against CPU-,GPU-,FPGA-,NDP-,and PIM-based platforms when processing numeric data *** also has 24.82×,32.94×,and 18.22×performance improvement when processing string data sets compared with CPU-,GPU-,and FPGA-based platforms.

关键词： ReCAM parallel sorting architecture design processing-in-memory

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Research on Practical Wireless Sensor Network Query Processing technology 2

Research on Practical Wireless Sensor Network Query Processi...

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2nd International Seminar on Computer Science and engineering technology, SCSET 2020

作者： Guo, Changjian Wu, Xiaoxuan School of Artificial Intelligence and Big Data Hefei University Hefei China Anhui Engineering Lab of Big Data Technology Application for Urban Infrastructure Hefei University Hefei China

WSN(Wireless Sensor Network) is intended for obtaining sensory data so that the query processing technology of high efficiency is the precondition of widely used WSN. Existing query processing technology assumes that the WSN deployed in two-dimensional or three-dimensional free space are not suitable for those deployed in such limited circumstances as roads, pipelines and indoor environments. This paper explores the problems of existing query processing technology, does research on perception data query processing method and technology, and seeks out the existing problem and its solution by means of using the WSN actually deployed in a building as an experimental platform. © Published under licence by IOP Publishing Ltd.

关键词： Query processing

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Research on Leak Location Method of Water Supply Network based on Deep Neural Network Model 3

Research on Leak Location Method of Water Supply Network bas...

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3rd International Seminar on Computer Science and engineering technology, SCSET 2022

作者： Wu, Xiaoxuan Zhang, Chen Hefei University School of Artificial Intelligence and Big Data Hefei China Anhui Engineering Lab of Big Data Technology Application for Urban Infrastructure Hefei University Hefei China

ISBN: (纸本)9781665478762

The water supply network is one of the important infrastructure in urban construction. It has strong theoretical and practical significance to realize the real-time monitoring and leak location of the water supply network. In this paper, based on the similarity of water supply network node pressure, fuzzy C-means clustering algorithm is used to realize the selection of finite monitoring points. On this basis, a depth neural network model is constructed according to the pressure changes of the monitoring points before and after the leakage of the water supply network, so as to locate the leakage points. In the experimental part, hydraulics simulation was conducted by using EPANETH pipe network adjustment software according to the layout structure of water supply network, and the pressure of all nodes was obtained. A deep neural network model was established by Keras in Tensorflow framework. After model training and testing, the training error was controlled within the effective range of 5 %. Finally, the model is applied to the actual leakage problem of underground water supply network in Langxi County of Xuancheng City, and the accurate location of the leakage point is realized. The experiment proves the feasibility and accuracy of the method proposed in this paper. © 2022 IEEE.

关键词： Neural network models

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Influence of nuclear physics inputs and astrophysical conditions on r-process

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Science China(Physics,Mechanics & Astronomy) 2019年第8期62卷 75-82页

作者： Zhu Li ZhongMing Niu BaoHua Sun School of Physics and Nuclear Energy Engineering Beihang University School of Physics and Materials Science Anhui University Institute of Physical Science and Information Technology Anhui University Beijing Advanced Innovation Center for Big Data-based Precision Medicine Beihang University

The rapid neutron-capture process(r-process) is one of the main mechanisms to explain the origin of heavy elements in the universe. Although the past decades have seen great progress in understanding this process, the related nuclear physics inputs to r-process models include significant uncertainty. In this study, ten nuclear mass models, including macroscopic, macroscopicmicroscopic, and microscopic models, are used to calculate the β-decay rates and neutron-capture rates of the neutron-rich isotopes for the r-process simulations occurring in three classes of astrophysical conditions. The final r-process abundances include uncertainties introduced by the nuclear mass model mainly through the variation of neutron-capture rates, whereas the uncertainties of β-decay rates make a relatively small contribution. The uncertainties in different astrophysical scenarios are also investigated,and are found to be connected to the diverse groups of nuclei produced during nucleosynthesis.

关键词： r-process nuclear masses β-decay rates neutron-capture rates

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Identification and mapping of soybean and maize crops based on Sentinel-2 data

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International Journal of Agricultural and Biological engineering 2020年第6期13卷 171-182页

作者： Bao She Yuying Yang Zhigen Zhao Linsheng Huang Dong Liang Dongyan Zhang School of Geomatics Anhui University of Science&TechnologyHuainan 232001AnhuiChina National Engineering Research Center for Agro-Ecological Big Data Analysis&Application Anhui UniversityHefei 230601China

Soybean and maize are important raw materials for the production of food and livestock *** mapping of these two crops is of great significance to crop management,yield estimation,and crop-damage *** this study,two towns in Guoyang County,anhui Province,China,were selected as the study area,and Sentinel-2 images were adopted to map the distributions of both crops in the 2019 growing *** data obtained on August 18(early pod-setting stage of soybean)was determined to be the most applicable to soybean and maize mapping by means of the Jeffries-Matusita(JM)***,three machine-learning algorithms,i.e.,random forest(RF),support vector machine(SVM)and back-propagation neural network(BPNN)were employed and their respective performance in crop identification was evaluated with the aid of 254 ground truth *** appeared that RF with a Kappa of 0.83 was superior to the other two ***,twenty candidate features containing the reflectance of ten spectral bands(spatial resolution at 10 m or 20 m)and ten remote-sensing indices were input into the RF algorithm to conduct an important *** features were screened out and served as the optimum subset,the mapping results of which were assessed based on the ground truth derived from the unmanned aerial vehicle(UAV)images covering six ground *** optimum feature-subset achieved high-accuracy crop mapping,with a reduction of data volume by 65%compared with the total twenty features,which also overrode the performance of ten spectral ***,feature-optimization had great potential in the identification of the two ***,the findings of this study can provide a valuable reference for mapping soybean and maize in areas with a fragmented landscape of farmland and complex planting structure.

关键词： soybean and maize crop identification Sentinel-2 data machine learning feature selection

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UniAdapter: All-in-One Control for Flexible Video Generation

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IEEE Transactions on Circuits and Systems for Video technology 2025年

作者： Wang, Cong Hu, Panwen Zhao, Haoyu Guo, Yuanfan Gu, Jiaxi Dong, Xiao Han, Jianhua Xu, Hang Liang, Xiaodan Chinese University of Hong Kong Hong Kong School of Science and Engineering Shenzhen China Fudan University School of Computer Science and Technology Shanghai China Huawei Noah'ark Lab Shanghai201206 China Sun Yat-Sen University School of Artificial Intelligence Zhuhai Campus Zhuhai519082 China Shenzhen Campus of Sun Yat-sen University School of Intelligent Systems Engineering Guangdong No. 66 Gongchang Road Guangming District Shenzhen518107 China Peng Cheng Laboratory and Guangdong Key Laboratory of Big Data Analysis and Processing Guangzhou510006 China

Condition-based video generation aims to create video content based on given information that describes specific subjects. However, most existing works can only utilize a single condition to guide the denoising process, thereby limiting their applicability to specific scenarios. Although some works attempt to accommodate multiple conditions within one framework, they often require multiple encoders, leading to inefficiencies in integrating multi-condition features. In this work, we present a framework that, with the support of the proposed Unified Adapter (UniAdapter), enables simultaneous multi-condition control of video generation within a single model. To effectively merge these conditions, we propose a novel Probabilistic Multi-condition Concatenator (PMC) module, which employs a unified encoder to accommodate multiple conditions and concatenate condition features at the pixel level to achieve fine-grained control. Following the PMC module, we employ 2D down-sampling blocks to refine features for injection into the Video Diffusion Model (VDM). Moreover, our UniAdapter is designed to be model-agnostic and compatible with any U-Net-based VDM, offering a versatile solution for improving video generation quality. Experimental results on public benchmarks UCF-101 and MSR-VTT show that our method achieves superior results in both quantitative and qualitative evaluations. © 2025 IEEE.

关键词： Signal encoding

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Answering reachability queries with ordered label constraints over labeled graphs

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Frontiers of Computer Science 2024年第1期18卷 105-117页

作者： Daoliang HE Pingpeng YUAN Hai JIN National Engineering Research Center for Big Data Technology and System Services Computing Technology and System LabCluster and Grid Computing LabSchool of Computer Science&TechnologyHuazhong University of Science and TechnologyWuhan 430074China

Reachability query plays a vital role in many graph analysis *** researches proposed many methods to efficiently answer reachability queries between vertex *** many real graphs are labeled graph,it highly demands label-Constrained Reachability(LCR)query inwhich constraint includes a set of labels besides vertex *** researches proposed several methods for answering some LCR queries which require appearance of some labels specified in constraints in the *** that constraint may be a label set,query constraint may be ordered labels,namely OLCR(Ordered-label-Constrained Reachability)queries which retrieve paths matching a sequence of ***,no solutions are available for ***,we propose DHL,a novel bloom filter based indexing technique for answering OLCR *** can be used to check reachability between vertex *** the answers are not no,then constrained DFS is ***,we employ DHL followed by performing constrained DFS to answer OLCR *** show that DHL has a bounded false positive rate,and it's powerful in saving indexing time and *** experiments on 10 real-life graphs and 12 synthetic graphs demonstrate that DHL achieves about 4.8-22.5 times smaller index space and 4.6-114 times less index construction time than two state-of-art techniques for LCR queries,while achieving comparable query response *** results also show that our algorithm can answer OLCR queries effectively.

关键词： graph ordered-label-constrained reachability partial index bloom filter query processing

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