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Deep learning for code generation: a survey

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Science China(Information Sciences) 2024年第9期67卷 5-40页

作者： Huangzhao ZHANG Kechi ZHANG Zhuo LI Jia LI Jia LI Yongmin LI Yunfei ZHAO Yuqi ZHU Fang LIU Ge LI Zhi JIN Key Lab of High Confidence Software Technologies (Peking university) Ministry of Education School of Computer Science Peking University School of Computer Science and Engineering Beihang University

In the past decade, thanks to the powerfulness of deep-learning techniques, we have witnessed a whole new era of automated code generation. To sort out developments, we have conducted a comprehensive review of solutions to deep learning-based code generation. In this survey, we generally formalize the pipeline and procedure of code generation and categorize existing solutions according to taxonomy from perspectives of architecture, model-agnostic enhancing strategy, metrics, and tasks. In addition, we outline the challenges faced by current dominant large models and list several plausible directions for future research. We hope that this survey may provide handy guidance to understanding, utilizing, and developing deep learning-based code-generation techniques for researchers and practitioners.

关键词： code generation automated software engineering deep learning large model artificial intelligence

Role of bonding filling on HER/OER/ORR multifunctional catalytic activity in transition-metals-doped PdPX(X=S,Se,Te)

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Rare Metals 2024年第10期43卷 5126-5140页

作者： Hai-Hua Huang Wei Li Cheng-Chao Hu Xue-Qin Sun Lin-Guo Lu Xiao-Feng Fan School of Materials Science and Engineering Laboratory of Sensitive Materials and DevicesShandong Department of EducationLiaocheng University School of Environmental and Material Engineering Yantai University Department of Physics University of Puerto Rico Key Laboratory of Automobile Materials (Jilin university) Ministry of EducationCollege of Materials Science and EngineeringJilin University

The development of stable and highly efficien multifunctional electrocatalysts for the hydrogen evolution reaction （HER）,oxygen reduction reaction （ORR） and oxygen evolution reaction （OER） are essential for the efficient conversion and storage of renewable *** significant advantages of single-atom catalysts,such as strong metal slab interactions,unsaturated coordination and efficient atomic utilization,have opened new avenues for designing multifunctional ***,based on density functional theory,a single atom doped PdPX system was designed as a multifunctional electrocatalyst,which demonstrated the synergistic effect between defects and transition metal atoms and led to enhanced catalytic *** results showed that PdPS/PdPSe with P/X vacancy,PdPTe with P/Pd vacancy and Co/Rh/Ir@PdPX exhibited promising HER ***@PdPS（Se）,with an overpotential of 0.56（0.44） V,was predicted to be a promising OER ***,Rh（Ir）@PdPS（Se）catalysts exhibited efficient catalytic properties for ORR Besides,Co@PdPS（Se）,Rh（Ir）@PdPSV（S）,Co@PdP-SeV（Se）and Ir@PdPSV（S）-1exihibited multifunctional catalytic performance with moderate ***,the origin of catalytic activity was revealed by using the crystal orbital Hamilton populations *** a strong adsorption system,proper filling of the anti-bonding state can increase the energy of the system,weaken the adsorption strength,and facilitate the desorption of intermediates Conversely,augmenting bonding states can enhance its adsorption *** findings provide theoretica guidance for the design and fabrication of novel multifunctional electrocatalysts in terms of filling of bondingstate.

关键词： Density functional theory Electrocatalyst Two-dimensional PdPX Water splitting

FlowGANAnomaly: Flow-Based Anomaly Network Intrusion Detection with Adversarial Learning

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Chinese Journal of Electronics 2024年第1期33卷 58-71页

作者： Zeyi LI Pan WANG Zixuan WANG School of Computer Science Nanjing University of Posts and Telecommunications School of Modern Posts Nanjing University of Posts and Telecommunications School of Internet of Things Nanjing University of Posts and Telecommunications

In recent years, low recall rates and high dependencies on data labelling have become the biggest obstacle to developing deep anomaly detection(DAD) techniques. Inspired by the success of generative adversarial networks(GANs) in detecting anomalies in computer vision and imaging, we propose an anomaly detection model called Flow GANAnomaly for detecting anomalous traffic in network intrusion detection systems(NIDS). Unlike traditional GAN-based approaches, which are composed of a flow encoder, a convolutional encoder-decoder-encoder, a flow decoder and a convolutional encoder, the architecture of this model consists of a generator(G) and a discriminator(D).Flow GANAnomaly maps the different types of traffic feature data from separate datasets to a uniform feature space,thus can capture the normality of network traffic data more accurately in an adversarial manner to mitigate the problem of the high dependence on data labeling. Moreover, instead of simply detecting the anomalies by the output of D, we proposed a new anomaly scoring method that integrates the deviation between the output of two Gs’ convolutional encoders with the output of D as weighted scores to improve the low recall rate of anomaly detection. We conducted several experiments comparing existing machine learning algorithms and existing deep learning methods(Auto Encoder and VAE) on four public datasets(NSL-KDD, CIC-IDS2017, CIC-DDo S2019, and UNSW-NB15). The evaluation results show that Flow GANAnomaly can significantly improve the performance of anomaly-based NIDS.

关键词： Deep learning Machine learning algorithms Computational modeling Network intrusion detection Imaging Telecommunication traffic Generative adversarial networks

Launching of a special column on the “Top 10 Academic Advances of Young Scholars at Zhejiang university”

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Journal of Zhejiang university-Science A(Applied Physics & Engineering) 2024年第10期25卷 763-764页

作者： Yunmin CHEN Academic Committee of Zhejiang university

Zhejiang university is home to 1700 young faculty members and scholars, who serve as the backbone driving the university's future academic innovation and development. To foster the growth and academic progress of these young scholars, the Academic Committee of Zhejiang university launched the “Top 10 Academic Advances of Young Scholars at Zhejiang university” project in January 2023.

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Investigation of coupling effect on the evolution of Richtmyer-Meshkov instability at double heavy square bubbles

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Science China(Physics,Mechanics & Astronomy) 2024年第1期67卷 52-70页

作者： Satyvir Singh Dhouha Taib Jalleli Applied and Computational Mathematics RWTH Aachen UniversityAachen 52056Germany Department of Mathematics Graphic Era Deemed to be UniversityDehradun 244712India Mathematics Department University College in DarbJazan UniversityAbu As Sadad 89653Saudi Arabia

This study investigates numerically the coupling effect on the evolution of Richtmyer-Meshkov instability at double heavy square *** scenarios are considered,each with varying initial separations S/L(where L demotes the side length of the square)ranging from 0.125 to *** are filled with SF6gas,and are enclosed by *** simulations of shock-induced multispecies flow are performed by solving the two-dimensional compressible Euler equations with a higher-order explicit modal discontinuous Galerkin *** simulations demonstrate that the flow morphology resulting from the coupling effect is highly dependent on the separation between two *** the separation is large,the squares experience a weaker coupling effect and evolve ***,as the separation reduces,the coupling effect manifests earlier in the interaction and becomes more *** a result,this phenomenon greatly intensifies the motion of inner upstream/downstream vortex rings towards the symmetry axis,leading to the emergence of multiple jets such as the twisted downward,upward,and coupled jets.A thorough exploration of the coupling effect of double squares is conducted by analyzing the vorticity ***,a significant quantity of vorticity is produced along the squares interface for smaller ***,these coupling effects result in various interface features(upstream/downstream movement,and height/width evolution),and temporal variations of various spatially integrated ***,the analysis of the flow structure also considers the interaction between two more flow parameters,the Mach and Atwood numbers,in order to evaluate the coupling effects.

关键词： RM instability shock wave double square bubbles coupling effect

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Large circuit models: opportunities and challenges

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Science China(Information Sciences) 2024年第10期67卷 25-66页

作者： Lei CHEN Yiqi CHEN Zhufei CHU Wenji FANG Tsung-Yi HO Ru HUANG Yu HUANG Sadaf KHAN Min LI Xingquan LI Yu LI Yun LIANG Jinwei LIU Yi LIU Yibo LIN Guojie LUO Hongyang PAN Zhengyuan SHI Guangyu SUN Dimitrios TSARAS Runsheng WANG Ziyi WANG Xinming WEI Zhiyao XIE Qiang XU Chenhao XUE Junchi YAN Jun YANG Bei YU Mingxuan YUAN Evangeline F.Y.YOUNG Xuan ZENG Haoyi ZHANG Zuodong ZHANG Yuxiang ZHAO Hui-Ling ZHEN Ziyang ZHENG Binwu ZHU Keren ZHU Sunan ZOU Huawei Noah’s Ark Lab School of Integrated Circuits Peking University Faculty of Electrical Engineering and Computer Science Ningbo University Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Department of Computer Science and Engineering The Chinese University of Hong Kong School of Integrated Circuits Southeast University Huawei HiSilicon Peng Cheng Laboratory School of Computer Science Peking University School of Microelectronics State Key Laboratory of Integrated Chips and System Fudan University School of Artificial Intelligence Shanghai Jiao Tong University

Within the electronic design automation(EDA) domain, artificial intelligence(AI)-driven solutions have emerged as formidable tools, yet they typically augment rather than redefine existing methodologies. These solutions often repurpose deep learning models from other domains, such as vision, text, and graph analytics, applying them to circuit design without tailoring to the unique complexities of electronic circuits. Such an “AI4EDA” approach falls short of achieving a holistic design synthesis and understanding,overlooking the intricate interplay of electrical, logical, and physical facets of circuit data. This study argues for a paradigm shift from AI4EDA towards AI-rooted EDA from the ground up, integrating AI at the core of the design process. Pivotal to this vision is the development of a multimodal circuit representation learning technique, poised to provide a comprehensive understanding by harmonizing and extracting insights from varied data sources, such as functional specifications, register-transfer level(RTL) designs, circuit netlists,and physical layouts. We champion the creation of large circuit models(LCMs) that are inherently multimodal, crafted to decode and express the rich semantics and structures of circuit data, thus fostering more resilient, efficient, and inventive design methodologies. Embracing this AI-rooted philosophy, we foresee a trajectory that transcends the current innovation plateau in EDA, igniting a profound “shift-left” in electronic design methodology. The envisioned advancements herald not just an evolution of existing EDA tools but a revolution, giving rise to novel instruments of design-tools that promise to radically enhance design productivity and inaugurate a new epoch where the optimization of circuit performance, power, and area(PPA) is achieved not incrementally, but through leaps that redefine the benchmarks of electronic systems' capabilities.

关键词： AI-rooted EDA large circuit models (LCMs) multimodal circuit representation learning circuit optimization

Symmetry quantification and segmentation in STEM imaging through Zernike moments

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Chinese Physics B 2024年第8期33卷 39-48页

作者： Jiadong Dan Cheng Zhang 赵晓续 N.Duane Loh Department of Biological Sciences National University of SingaporeSingapore Center for Bioimaging Sciences(CBIS) National University of SingaporeSingapore Department of Physics National University of SingaporeSingapore School of Materials Science and Engineering Peking UniversityBeijing 100871China

We present a method using Zernike moments for quantifying rotational and reflectional symmetries in scanning transmission electron microscopy(STEM)images,aimed at improving structural analysis of materials at the atomic *** technique is effective against common imaging noises and is potentially suited for low-dose imaging and identifying quantum *** showcase its utility in the unsupervised segmentation of polytypes in a twisted bilayer TaS_(2),enabling accurate differentiation of structural phases and monitoring transitions caused by electron beam *** approach enhances the analysis of structural variations in crystalline materials,marking a notable advancement in the characterization of structures in materials science.

关键词： scanning transmission electron microscopy(STEM) symmetry segmentation

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High-Performance Flow Classification of Big Data Using Hybrid CPU-GPU Clusters of Cloud Environments

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Tsinghua Science and Technology 2024年第4期29卷 1118-1137页

作者： Azam Fazel-Najafabadi Mahdi Abbasi Hani H.Attar Ayman Amer Amir Taherkordi Azad Shokrollahi Mohammad R.Khosravi Ahmed A.Solyman Department of Computer Engineering Faculty of EngineeringBu-Ali Sina UniversityHamedan ***Iran Department of Energy Engineering Zarqa UniversityZarqa 13132Jordan Department of Informatics University of OsloOslo 0316Norway Department of Computer Science MalmöUniversityMalmö20506Sweden Shandong Provincial university Laboratory for Protected Horticulture Weifang University of Science and TechnologyWeifang 261100China Department of Electrical and Electronics Engineering NişantaşıUniversityIstanbul 34481742Türkiye

The network switches in the data plane of Software Defined Networking (SDN) are empowered by an elementary process, in which enormous number of packets which resemble big volumes of data are classified into specific flows by matching them against a set of dynamic rules. This basic process accelerates the processing of data, so that instead of processing singular packets repeatedly, corresponding actions are performed on corresponding flows of packets. In this paper, first, we address limitations on a typical packet classification algorithm like Tuple Space Search (TSS). Then, we present a set of different scenarios to parallelize it on different parallel processing platforms, including Graphics Processing Units (GPUs), clusters of Central Processing Units (CPUs), and hybrid clusters. Experimental results show that the hybrid cluster provides the best platform for parallelizing packet classification algorithms, which promises the average throughput rate of 4.2 Million packets per second (Mpps). That is, the hybrid cluster produced by the integration of Compute Unified Device Architecture (CUDA), Message Passing Interface (MPI), and OpenMP programming model could classify 0.24 million packets per second more than the GPU cluster scheme. Such a packet classifier satisfies the required processing speed in the programmable network systems that would be used to communicate big medical data.

关键词： OpenMP Compute Unified Device Architecture(CUDA) Message Passing Interface(MPI) packet classification medical data tuple space algorithm Graphics Processing Unit(GPU)cluster

Davidson base as an appropriate base for the shell model in the case of 1p- and 1h- nuclei

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Communications in Theoretical Physics 2024年第10期76卷 94-100页

作者： Hadi Sobhani Yan-An Luo Amir Jalili Hassan Hassanabadi School of Physics Nankai University Department of Physics Zhejiang Sci-Tech University Institute of Theoretical Physics Faculty of Physics University of Warsaw Institute of Actuarial Science and Data Analytics UCSI University

This study endeavors to develop an improved set of basis functions for nuclear shell-model calculations. The shell model, a well-established approach to understanding nuclear structure,typically employs the harmonic oscillator potential within the mean-field approximation. Given the extensive validation and consistency of harmonic oscillator results with experimental data,we propose a modification by incorporating a centrifugal term that converges toward the Davidson potential. This potential has been extensively studied, and we aim to extract relevant experimental data for the simplest cases in the shell model, namely one-particle and one-hole nuclei. A comprehensive comparison between the Davidson-based results and the harmonic oscillator calculations is presented to demonstrate the effectiveness of the new basis functions.

关键词： beta decay gamma transition nuclear structure shell-model calculations