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QSobel:A novel quantum image edge extraction algorithm

science China(Information sciences) 2015年第1期58卷 107-119页

作者： ZHANG Yi LU Kai GAO YingHui Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology College of Computer National University of Defense Technology College of Electronic Science and Engineering National University of Defense Technology

Edge extraction is an indispensable task in digital image processing. With the sharp increase in the image data, real-time problem has become a limitation of the state of the art of edge extraction *** this paper, QSobel, a novel quantum image edge extraction algorithm is designed based on the flexible representation of quantum image(FRQI) and the famous edge extraction algorithm Sobel. Because FRQI utilizes the superposition state of qubit sequence to store all the pixels of an image, QSobel can calculate the Sobel gradients of the image intensity of all the pixels simultaneously. It is the main reason that QSobel can extract edges quite fast. Through designing and analyzing the quantum circuit of QSobel, we demonstrate that QSobel can extract edges in the computational complexity of O(n2) for a FRQI quantum image with a size of2 n × 2n. Compared with all the classical edge extraction algorithms and the existing quantum edge extraction algorithms, QSobel can utilize quantum parallel computation to reach a significant and exponential ***, QSobel would resolve the real-time problem of image edge extraction.

关键词： edge extraction quantum image processing FRQI Sobel computational complexity

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GPU acceleration of subgraph isomorphism search in large scale graph

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Journal of Central South University 2015年第6期22卷 2238-2249页

作者：杨博卢凯高颖慧王小平徐凯 Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology College of Computer National University of Defense Technology Department of Electronic Science and Engineering National University of Defense Technology

A novel framework for parallel subgraph isomorphism on GPUs is proposed, named GPUSI, which consists of GPU region exploration and GPU subgraph matching. The GPUSI iteratively enumerates subgraph instances and solves the subgraph isomorphism in a divide-and-conquer fashion. The framework completely relies on the graph traversal, and avoids the explicit join operation. Moreover, in order to improve its performance, a task-queue based method and the virtual-CSR graph structure are used to balance the workload among warps, and warp-centric programming model is used to balance the workload among threads in a warp. The prototype of GPUSI is implemented, and comprehensive experiments of various graph isomorphism operations are carried on diverse large graphs. The experiments clearly demonstrate that GPUSI has good scalability and can achieve speed-up of 1.4–2.6 compared to the state-of-the-art solutions.

关键词： parallel graph isomorphism GPU backtrack paradigm

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vSpec: workload-adaptive operating system specialization for virtual machines in cloud computing

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science China(Information sciences) 2016年第9期59卷 47-62页

作者： Xinkui ZHAO Jianwei YIN Zuoning CHEN Sheng HE College of Computer Science Zhejiang University National Parallel Computing Engineering Research Center Jiangnan Institute of Computing Technology

In general, operating systems(OSs) are designed to mediate access to device hardware by applications. They process different kinds of system calls using an indiscriminate kernel with the same *** in cloud computing platforms are constructed from service components. Each of the service components is assigned separately to an individual virtual machine(VM), which leads to homogeneous system calls on each VM. In addition, the requirements for kernel function and configuration of system parameters from different VMs are different. Therefore, the suit-to-all design incurs an unnecessary performance overhead and restricts the OS’s processing capacity in cloud computing. In this paper, we propose an adaptive model for cloud computing to resolve the conflict between generality and performance. Our model adaptively specializes the OS of a VM according to the resource-consuming characteristics of workloads on the VM. We implement a prototype of the adaptive model, v Spec. There are five classes of VM: CPU-intensive, memory-intensive, I/O-intensive, networkintensive and compound, according to the resource-consuming characteristics of the workloads running on the VMs. v Spec specializes the OS of a VM according to the VM class. We perform comprehensive experiments to evaluate the effectiveness of v Spec on benchmarks and real-world applications.

关键词： workload classification operating system specialization workload-aware cloud computing v Spec system performance

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Speeding up the MATLAB complex networks package using graphic processors

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Chinese Physics B 2011年第9期20卷 460-467页

作者：张百达唐玉华吴俊杰李鑫 National laboratory for Parallel and Distributed Processing School of ComputerNational University of Defense Technology Department of Computer Science and Technology School of ComputerNational University of Defense Technology

The availability of computers and communication networks allows us to gather and analyse data on a far larger scale than previously. At present, it is believed that statistics is a suitable method to analyse networks with millions, or more, of vertices. The MATLAB language, with its mass of statistical functions, is a good choice to rapidly realize an algorithm prototype of complex networks. The performance of the MATLAB codes can be further improved by using graphic processor units （GPU）. This paper presents the strategies and performance of the GPU implementation of a complex networks package, and the Jacket toolbox of MATLAB is used. Compared with some commercially available CPU implementations, GPU can achieve a speedup of, on average, 11.3x. The experimental result proves that the GPU platform combined with the MATLAB language is a good combination for complex network research.

关键词： complex networks graphic processors unit MATLAB Jacket Toolbox

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FAAD:an unsupervised fast and accurate anomaly detection method for a multi-dimensional sequence over data stream

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Frontiers of Information technology & Electronic Engineering 2019年第3期20卷 388-404页

作者： Bin LI Yi-jie WANG Dong-sheng YANG Yong-mou LI Xing-kong MA Science and Technology on Parallel and Distributed Processing Laboratory College of ComputerNational University of Defense Technology Block Chain Research Institute of LianLian Pay

Recently, sequence anomaly detection has been widely used in many fields. Sequence data in these fields are usually multi-dimensional over the data stream. It is a challenge to design an anomaly detection method for a multi-dimensional sequence over the data stream to satisfy the requirements of accuracy and high speed. It is because:(1) Redundant dimensions in sequence data and large state space lead to a poor ability for sequence modeling;(2) Anomaly detection cannot adapt to the high-speed nature of the data stream, especially when concept drift occurs, and it will reduce the detection rate. On one hand, most existing methods of sequence anomaly detection focus on the single-dimension sequence. On the other hand, some studies concerning multi-dimensional sequence concentrate mainly on the static database rather than the data stream. To improve the performance of anomaly detection for a multi-dimensional sequence over the data stream, we propose a novel unsupervised fast and accurate anomaly detection(FAAD) method which includes three algorithms. First, a method called "information calculation and minimum spanning tree cluster" is adopted to reduce redundant dimensions. Second, to speed up model construction and ensure the detection rate for the sequence over the data stream, we propose a method called"random sampling and subsequence partitioning based on the index probabilistic suffix tree." Last, the method called "anomaly buffer based on model dynamic adjustment" dramatically reduces the effects of concept drift in the data stream. FAAD is implemented on the streaming platform Storm to detect multi-dimensional log audit *** with the existing anomaly detection methods, FAAD has a good performance in detection rate and speed without being affected by concept drift.

关键词： Data stream Multi-dimensional sequence Anomaly detection Concept drift Feature selection

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DKNNS:Scalable and accurate distributed K nearest neighbor search for latency-sensitive applications

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science China(Information sciences) 2013年第3期56卷 123-139页

作者： FU YongQuan WANG YiJie National Key Laboratory for Parallel and Distributed Processing School of Computer ScienceNational University of Defense Technology

To reduce the access latencies of end hosts,latency-sensitive applications need to choose suitably close service machines to answer the access requests from end *** K nearest neighbor search locates K service machines closest to end hosts,which can efficiently optimize the access latencies for end *** work has weakness in terms of the accuracy and *** to the scalable and accurate K nearest neighbor search problem,we propose a distributed K nearest neighbor search method called DKNNS in this *** machines are organized into a locality-aware multilevel *** first locates a service machine that starts the search process based on a farthest neighbor search scheme,then discovers K nearest service machines based on a backtracking approach within the proximity region containing the target in the latency *** analysis,simulation results and deployment experiments on the PlanetLab show that,DKNNS can determine K approximately optimal service machines,with modest completion time and query ***,DKNNS is also quite stable that can be used for reducing frequent searches by caching found nearest neighbors.

关键词： latency sensitive network applications K nearest neighbor search network coordinate

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Tensor joint framework enhanced by game-theoretic constrained optimization for skin cancer forecasting

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Swarm and Evolutionary Computation 2025年 96卷

作者： Yang, Jinqian Wen, Jie Zhao, Haochen Cai, Jianghui Cai, Xingjuan Shanxi Key Laboratory of Big Data Analysis and Parallel Computing Taiyuan University of Science and Technology Taiyuan030024 China School of Computer Science and Technology Taiyuan University of Science and Technology Taiyuan030024 China School of Computer Science and Technology North University of China Taiyuan030051 China

Skin cancer is a public health concern due to its high incidence and detection challenges. While tensor decomposition is widely utilized to predict miRNA-disease associations, existing models are not optimized for skin cancer, thereby limiting their comprehensiveness and interpretability. To address these limitations, we propose a many-objective tensor joint framework aimed at enhancing prediction accuracy while maintaining comprehensiveness and interpretability. The proposed framework classifies tensors according to their similarity to skin cancer and employs a many-objective optimization algorithm to optimize weight allocation. Similarity constraints for skin cancer are applied to prioritize relevant information, effectively minimizing noise from unrelated diseases. Furthermore, we introduce a multi-stage constrained many-objective optimization algorithm based on game theory. This algorithm leverages game theory to dynamically adjust population diversity, convergence, and constraint violations throughout the evolutionary process, thereby improving the overall framework's performance. Experimental results demonstrate that the proposed algorithm outperforms existing state-of-the-art constrained many-objective optimization algorithms on benchmarks such as MW and DTLZ. Compared to other tensor decomposition methods, the proposed framework achieves a comprehensive improvement ranging from 8.49% to 11.53% across four objectives. © 2025

关键词： Cellular automata

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Simulation study of N-hit SET variation in differential cascade voltage switch logical circuits

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science China(Information sciences) 2015年第2期58卷 165-173页

作者： HUANG PengCheng CHEN ShuMing CHEN JianJun WU ZhenYu LIANG ZhengFa HU ChunMei LIANG Bin LIU BiWei Micro-electronics and Microprocessor Institute College of Computer ScienceNational University of Defense Technology National Laboratory for Parallel and Distributed Processing College of Computer ScienceNational University of Defense Technology

The advancement in the process leads to more concern about the Single Event(SE) sensitivity of the Differential Cascade Voltage Switch Logic(DCVSL) circuits. The simulation results indicate that the Single Event Transient(SET) generated at the DCVSL gate is much larger than that at the ordinary CMOS gate, and their SET variation is different. Based on charge collection, in this paper, the effective collection time theory is proposed to set forth the SET pulse generated at the DCVSL gate. Through 3D TCAD mixed-mode simulation in 65 nm twin-well bulk CMOS process, the effects on SET variation of device parameters such as well contact size and environment parameters such as voltage are investigated.

关键词： differential cascade voltage switch logic(DCVSL) single event transient(SET) effective collection time pulse feedback feature(PFF) across-coupled structure

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SPICE modeling of memristors with multilevel resistance states

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Chinese Physics B 2012年第9期21卷 594-600页

作者：方旭东唐玉华吴俊杰 National Laboratory for Parallel and Distributed Processing School of ComputerNational University of Defense Technology Department of Computer Science and Technology School of ComputerNational University of Defense Technology

With CMOS technologies approaching the scaling ceiling, novel memory technologies have thrived in recent years, among which the memristor is a rather promising candidate for future resistive memory （RRAM）. Memristor＇s potential to store multiple bits of information as different resistance levels allows its application in multilevel cell （MCL） tech- nology, which can significantly increase the memory capacity. However, most existing memristor models are built for binary or continuous memristance switching. In this paper, we propose the simulation program with integrated circuits emphasis （SPICE） modeling of charge-controlled and flux-controlled memristors with multilevel resistance states based on the memristance versus state map. In our model, the memristance switches abruptly between neighboring resistance states. The proposed model allows users to easily set the number of the resistance levels as parameters, and provides the predictability of resistance switching time if the input current/voltage waveform is given. The functionality of our models has been validated in HSPICE. The models can be used in multilevel RRAM modeling as well as in artificial neural network simulations.

关键词： memristor multilevel cell SPICE model

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Betweenness-based algorithm for a partition scale-free graph

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Chinese Physics B 2011年第11期20卷 556-564页

作者：张百达吴俊杰唐玉华周静 National Laboratory for Parallel and Distributed Processing School of ComputersNational University of Defense Technology Department of Computer Science and Technology School of ComputersNational University of Defense Technology

Many real-world networks are found to be scale-free. However, graph partition technology, as a technology capable of parallel computing, performs poorly when scale-free graphs are provided. The reason for this is that traditional partitioning algorithms are designed for random networks and regular networks, rather than for scale-free networks. Multilevel graph-partitioning algorithms are currently considered to be the state of the art and are used extensively. In this paper, we analyse the reasons why traditional multilevel graph-partitioning algorithms perform poorly and present a new multilevel graph-partitioning paradigm, top down partitioning, which derives its name from the comparison with the traditional bottom-up partitioning. A new multilevel partitioning algorithm, named betweenness-based partitioning algorithm, is also presented as an implementation of top-down partitioning paradigm. An experimental evaluation of seven different real-world scale-free networks shows that the betweenness-based partitioning algorithm significantly outperforms the existing state-of-the-art approaches.

关键词： graph partitioning betweenness-based partitioning algorithm scale free network

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