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Block-gram:Mining knowledgeable features for efficiently smart contract vulnerability detection

Digital Communications and Networks 2025年第1期11卷 1-12页

作者： Xueshuo Xie Haolong Wang Zhaolong Jian Yaozheng Fang Zichun Wang Tao Li Tianjin Key Laboratory of Network and Data Security Technology TianjinChina College of Computer Science Nankai UniversityTianjinChina Key Laboratory of Blockchain and Cyberspace Governance of Zhejiang Province China State Key Laboratory of Computer Architecture Institute of Computing TechnologyChinese Academy of SciencesChina

Smart contracts are widely used on the blockchain to implement complex transactions,such as decentralized applications on *** vulnerability detection of large-scale smart contracts is critical,as attacks on smart contracts often cause huge economic *** it is difficult to repair and update smart contracts,it is necessary to find the vulnerabilities before they are ***,code analysis,which requires traversal paths,and learning methods,which require many features to be trained,are too time-consuming to detect large-scale on-chain ***-based methods will obtain detection models from a feature space compared to code analysis methods such as symbol *** the existing features lack the interpretability of the detection results and training model,even worse,the large-scale feature space also affects the efficiency of *** paper focuses on improving the detection efficiency by reducing the dimension of the features,combined with expert *** this paper,a feature extraction model Block-gram is proposed to form low-dimensional knowledge-based features from ***,the metadata is separated and the runtime code is converted into a sequence of opcodes,which are divided into segments based on some instructions(jumps,etc.).Then,scalable Block-gram features,including 4-dimensional block features and 8-dimensional attribute features,are mined for the learning-based model ***,feature contributions are calculated from SHAP values to measure the relationship between our features and the results of the detection *** addition,six types of vulnerability labels are made on a dataset containing 33,885 contracts,and these knowledge-based features are evaluated using seven state-of-the-art learning algorithms,which show that the average detection latency speeds up 25×to 650×,compared with the features extracted by N-gram,and also can enhance the interpretability of the detection model.

关键词： Smart contract Bytecode&opcode Knowledgeable features Vulnerability detection Feature contribution

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A fully connected polarization-entangled network via integrated spontaneous four-wave mixing engineering

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Science China(Physics,Mechanics & Astronomy) 2025年第6期Mechanics & Astronomy) .卷 76-83页

作者： Pingyu Zhu Yan Wang Yuxing Du Miaomiao Yu Kaikai Zhang Kun Wang Ping Xu Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer Science and TechnologyNational University of Defense Technology Hefei National Laboratory

Quantum communication is rapidly developing and is gradually being commercialized due to its technological maturity. Establishing dense communication links among multiple users in a scalable and efficient way is of great significance for realizing a large-scale quantum communication network. Here, we propose a novel scheme to construct a fully connected polarizationentangled network, utilizing the engineering of spontaneous four-wave mixings(SFWMs) and a path-polarization converter. It does not require active optical switches which limit the communication speed, or trusted nodes which lead to potential security risks. The required frequency channels in the network grow linearly with the number of users. We experimentally demonstrate a six-user fully connected network with on-chip SFWM processes motivated by four pumps. Each user in the network receives a frequency channel, and all fifteen connections between the users are implemented simultaneously. Our work opens up a promising scheme to efficiently construct fully connected large-scale networks.

关键词： quantum network quantum entanglement nonlinear optics integrated optics

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The quantum Ising model for perfect matching and solving it with variational quantum eigensolver

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Science China(Information Sciences) 2024年第9期67卷 306-320页

作者： Qilin ZHENG Pingyu ZHU Chao WU Miaomiao YU Weihong LUO Ping XU Institute for Quantum Information and State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Hefei National Laboratory

Obtaining all perfect matchings of a graph is a tough problem in graph theory, and its complexity belongs to the #P-Complete class. The problem is closely related to combinatorics, marriage matching problems, dense subgraphs, the Gaussian boson sampling, chemical molecular structures, and dimer *** this paper, we propose a quadratic unconstrained binary optimization formula of the perfect matching problem and translate it into the quantum Ising model. We can obtain all perfect matchings by mapping them to the ground state of the quantum Ising Hamiltonian and solving it with the variational quantum eigensolver. Adjusting the model's parameters can also achieve the maximum or minimum weighted perfect matching. The experimental results on a superconducting quantum computer of the Origin Quantum computing technology Company show that our model can encode 2~n dimensional optimization space with only O（n） qubits consumption and achieve a high success probability of the ground state corresponding to all perfect matchings. In addition, the further simulation results show that the model can support a scale of more than 14 qubits, effectively resist the adverse effects of noise, and obtain a high success probability at a shallow variational depth. This method can be extended to other combinatorial optimization problems.

关键词： perfect matching Ising model quantum Hamiltonian variational quantum eigensolver quadratic unconstrained binary optimization

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Improving DNN Accuracy on MLC PIM via Black-box Fine-tuning

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IEEE Transactions on computer-Aided Design of Integrated Circuits and Systems 2024年第6期44卷 2277-2286页

作者： Lv, Hao Zhang, Lei Wang, Ying Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing100089 China The State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing100089 China

Resistive random access memory (RRAM) emerges as a promising technology for developing energy-efficient deep neural network (DNN) accelerators, owing to its analog computing paradigm for matrix-vector multiplication. However, the inherent non-ideal device features of RRAM cells, such as device variation, read disturbances, and limited on/off ratio, present challenges for model deployment. Therefore, to ensure accurate storage and computing precision for RRAM-based accelerators, a widely used practice is encoding a DNN weight by multiple cells, resulting in significant memory overhead and underutilization. This challenge is further exacerbated by the rapid increases in model size witnessed in recent years. While the one-to-one weight-cell mapping strategy can improve memory utilization, it inevitably introduces deviations in the mapped DNN weight from the desired value due to RRAM variation issues, leading to model accuracy degradation. In response to this challenge, we abstract the model optimization on RRAM chips as a black-box optimization problem, aimed at optimizing model accuracy without the requirement of precise weight programming. We systematically analyze the model optimization behavior on multi-level RRAM devices by investigating the accuracy recovery process of various fine-tuning strategies in recovering model performance under the black-box setting. Based on the analysis, we propose a black-box finetune scheme to recover the model performance for multilevel RRAM under the black-box setting. Our proposed scheme leverages knowledge distillation and exploits input/output information of the model on RRAM to guide the fine-tuning process, finally restoring its accuracy. Experimental results demonstrate the efficacy of our black-box fine-tuning scheme, achieving nearly complete recovery of model performance. Our approach yields over a 3% improvement in model accuracy compared to variation-aware training approaches. © 1982-2012 IEEE.

关键词： Energy efficiency

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Four-wave mixing Bragg scattering for small frequency shift from silicon coupled microrings

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Chinese Physics B 2025年第1期34卷 351-355页

作者： Chang Zhao Chao Wu Pingyu Zhu Yuxing Du Yan Wang Miaomiao Yu Kaikai Zhang Ping Xu Institute for Quantum Information&State Key Laboratory of High Performance Computing College of Computer Science and TechnologyNational University of Defense TechnologyChangsha 410073China

Frequency conversion is pivotal in nonlinear optics and quantum optics for manipulating and translating light signals across different wavelength *** frequency conversion between two light beams with a small frequency interval is a central *** this work,we design a pair of coupled silicon microrings wherein coupled-induced modesplitting exists to achieve a small frequency shift by the process of four-wave mixing Bragg *** an example,the signal can be up or down converted to the idler which is 15.5 GHz spaced when two pumps align with another pair of split *** results unveil the potential of coupled microring resonators for small interval frequency conversion in a high-fidelity,all-optical,and signal processing quantum frequency interface.

关键词： four-wave mixing Bragg scattering silicon coupled microrings

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On-chip quantum NOON state sensing for temperature and humidity

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Chinese Physics B 2024年第10期33卷 15-20页

作者： Weihong Luo Chao Wu Yuxing Du Chang Zhao Miaomiao Yu Pingyu Zhu Kaikai Zhang Ping Xu Institute for Quantum Information&State Key Laboratory of High Performance Computing College of Computer Science and TechnologyNational University of Defense TechnologyChangsha 410073China

A maximal photon number entangled state,namely NOON state,can be adopted for sensing with a quantum *** this work,we designed silicon quantum photonic chips containing two types of Mach-Zehnder interferometerswherein the two-photon NOON state,sensing element for temperature or humidity,is *** with classicallight or single photon case,two-photon NOON state sensing shows a solid enhancement in the sensing resolution *** the first demonstration of on-chip quantum photonic sensing,it reveals the advantages of photonic chips forhigh integration density,small-size,stability for multiple-parameter sensing serviceability.A higher sensing precision isexpected to beat the standard quantum limit with a higher photon number NOON state.

关键词： quantum sensing NOON state photonic chip

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Solving the subset sum problem by the quantum Ising model with variational quantum optimization based on conditional values at risk

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Science China(Physics,Mechanics & Astronomy) 2024年第8期67卷 43-55页

作者： Qilin Zheng Miaomiao Yu Pingyu Zhu Yan Wang Weihong Luo Ping Xu Institute for Quantum Information and State Key Laboratory of High Performance Computing College of Computer Science and TechnologyNational University of Defense TechnologyChangsha 410073China Hefei National Laboratory Hefei 230088China

The subset sum problem is a combinatorial optimization problem,and its complexity belongs to the nondeterministic polynomial time complete(NP-Complete)*** problem is widely used in encryption,planning or scheduling,and integer *** accurate search algorithm with polynomial time complexity has not been found,which makes it challenging to be solved on classical *** effectively solve this problem,we translate it into the quantum Ising model and solve it with a variational quantum optimization method based on conditional values at *** proposed model needs only n qubits to encode 2ndimensional search space,which can effectively save the encoding quantum *** model inherits the advantages of variational quantum algorithms and can obtain good performance at shallow circuit depths while being robust to noise,and it is convenient to be deployed in the Noisy Intermediate Scale Quantum *** investigate the effects of the scalability,the variational ansatz type,the variational depth,and noise on the ***,we also discuss the performance of the model under different conditional values at *** computer simulation,the scale can reach more than nine *** selecting the noise type,we construct simulators with different QVs and study the performance of the model with *** addition,we deploy the model on a superconducting quantum computer of the Origin Quantum technology Company and successfully solve the subset sum *** model provides a new perspective for solving the subset sum problem.

关键词： subset sum problem quantum Ising model conditional values at risk variational quantum optimization

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Automatic architecture design for distributed quantum computing

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Chinese Physics B 2024年第12期33卷 45-59页

作者： Ting-Yu Luo Yu-Zhen Zheng Xiang Fu Yu-Xin Deng Shanghai Key Laboratory of Trustworthy Computing East China Normal UniversityShanghai 200062China Institute for Quantum Information&State Key Laboratory of High Performance Computing College of ComputerNational University of Defense TechnologyChangsha 410073China Tianjin Institute of Advanced Technology Tianjin 300459China

In distributed quantum computing(DQC),quantum hardware design mainly focuses on providing as many as possible high-quality inter-chip ***,quantum software tries its best to reduce the required number of remote quantum gates between ***,this“hardware first,software follows”methodology may not fully exploit the potential of *** by classical software-hardware co-design,this paper explores the design space of application-specific DQC *** specifically,we propose Auto Arch,an automated quantum chip network(QCN)structure design *** qubits grouping followed by a customized QCN design,AutoArch can generate a near-optimal DQC architecture suitable for target quantum *** results show that the DQC architecture generated by Auto Arch can outperform other general QCN architectures when executing target quantum algorithms.

关键词： distributed quantum computing quantum architecture quantum circuit partitioning

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BTBench: A Benchmark for Comprehensive Binary Translation Performance Evaluation

BTBench: A Benchmark for Comprehensive Binary Translation Pe...

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2024 IEEE International Symposium on Performance Analysis of Systems and Software, ISPASS 2024

作者： Li, Xinyu Lan, Yanzhi Niu, Gen Xue, Feng Zhang, Fuxin Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences State Key Laboratory of Computer Architecture China

ISBN: (纸本)9798350376388

Binary translation serves as a fundamental technol-ogy for instruction set emulation, system virtualization, runtime instrumentation, and numerous other applications. Many techniques have been proposed to enhance the efficiency of binary translation systems. However, imprecise performance evaluation leads to potential performance shortcomings of binary translators in real-world applications. Previous studies primarily employ CPU benchmarks, which may overlook performance issues spe-cific to binary translators and fail to guide for optimizing binary translation. To address this issue, we propose a new benchmark suite named BTBench(Binary Translation Benchmark), which provides a convenient, portable, and comprehensive solution. BT-Bench takes into account the inherent attributes of binary trans-lators, such as translation and code-cache lookup overhead. We carefully select benchmarks that offer comprehensive coverage and align with real-world application scenarios. To validate the effectiveness of BTBench, we conducted rigorous experimentation on four widely-used binary translators. The analysis of the results reveals that, compared to existing CPU benchmarks, BTBench is better suited for identifying potential performance shortcomings, providing invaluable insights for future optimization efforts. The BTBench benchmark suite is publicly available 1 • © 2024 IEEE.

关键词： Benchmarking

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Multiuser Computation Offloading for Long-Term Sequential Tasks in Mobile Edge computing Environments

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Tsinghua Science and technology 2023年第1期28卷 93-104页

作者： Huanhuan Xu Jingya Zhou Wenqi Wei Baolei Cheng School of Computer Science and Technology Soochow UniversitySuzhou 215006China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214125China Provincial Key Laboratory for Computer Information Processing Technology Soochow UniversitySuzhou 215006China School of Computer Science Georgia Institute of TechnologyAtlantaGA 30332USA

Mobile edge computing has shown its potential in serving emerging latency-sensitive mobile applications in ultra-dense 5G networks via offloading computation workloads from the remote cloud data center to the nearby network ***,current computation offloading studies in the heterogeneous edge environment face multifaceted challenges:Dependencies among computational tasks,resource competition among multiple users,and diverse long-term *** applications typically consist of several functionalities,and one huge category of the applications can be viewed as a series of sequential *** this study,we first proposed a novel multiuser computation offloading framework for long-term sequential ***,we presented a comprehensive analysis of the task offloading process in the framework and formally defined the multiuser sequential task offloading ***,we decoupled the long-term offloading problem into multiple single time slot offloading problems and proposed a novel adaptive method to solve *** further showed the substantial performance advantage of our proposed method on the basis of extensive experiments.

关键词： mobile edge computing sequential tasks computation offloading dependency

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