Ethernet over SDH/SONET (EOS) is a hotspot in today's data transmission technology for it combines the merits of both Ethernet and SDH/SONET. However, implementing an EOS system on a chip is complex and needs full...Ethernet over SDH/SONET (EOS) is a hotspot in today's data transmission technology for it combines the merits of both Ethernet and SDH/SONET. However, implementing an EOS system on a chip is complex and needs full verifications. This paper introduces our design of Hardware/Software co-verification platform for EOS design. The hardware platform contains a microprocessor board and an FPGA (Field Programmable Gate Array)-based verification board, and the corresponding software includes test benches running in FPGAs, controlling programs for the microprocessor and a console program with GUI (Graphical User Interface) interface for configuration, management and supervision. The design is cost-effective and has been successfully employed to verify several IP (Intellectual Property) blocks of our EOS chip. Moreover, it is flexible and can be applied as a general-purpose verification platform.展开更多
In this paper, the storage capacity of communication among cores and processors is taken into account and a maximum D-value-first algorithm is proposed. By improving the hardware parallelism in the task execution proc...In this paper, the storage capacity of communication among cores and processors is taken into account and a maximum D-value-first algorithm is proposed. By improving the hardware parallelism in the task execution process, the maximum storage requirements for communication are minimized. Experimental results with various directed acyclic graph models showed that compared with the earliest-task-first algorithm, the storage requirements for communication were reduced by 22.46%, on average, while the average of makespan only increased by 0.82%,.展开更多
This paper presents an algorithm that combines the chaos optimization algorithm with the maximum entropy ( COA-ME) by using entropy model based on chaos algorithm,in which the maximum entropy is used as the second met...This paper presents an algorithm that combines the chaos optimization algorithm with the maximum entropy ( COA-ME) by using entropy model based on chaos algorithm,in which the maximum entropy is used as the second method of searching the excellent solution. The search direction is improved by chaos optimization algorithm and realizes the selective acceptance of wrong solution. The experimental result shows that the presented algorithm can be used in the partitioning of hardware/software of reconfigurable system. It effectively reduces the local extremum problem,and search speed as well as performance of partitioning is improved.展开更多
In order to improve the efficiency of embedded software running on processor core, this paper proposes a hard-ware/software co-optimization approach for embedded software from the system point of view. The proposed st...In order to improve the efficiency of embedded software running on processor core, this paper proposes a hard-ware/software co-optimization approach for embedded software from the system point of view. The proposed stepwise methods aim at exploiting the structure and the resources of the processor as much as possible for software algorithm optimization. To achieve low memory usage and low frequency need for the same performance, this co-optimization approach was used to optimize embedded software of MP3 decoder based on a 16-bit fixed-point DSP core. After the optimization, the results of decoding 128 kbps, 44.1 kHz stereo MP3 on DSP evaluation platform need 45.9 MIPS and 20.4 kbytes memory space. The optimization rate achieves 65.6% for memory and 49.6% for frequency respectively compared with the results by compiler using floating-point computation. The experimental result indicates the availability of the hardware/software co-optimization approach depending on the algorithm and architecture.展开更多
This paper deals with a new hardware/software embedded system design methodology based on design pattern approach by development of a new design tool called smartcell. Three main constraints of embedded systems design...This paper deals with a new hardware/software embedded system design methodology based on design pattern approach by development of a new design tool called smartcell. Three main constraints of embedded systems design process are investigated: the complexity, the partitioning between hardware and software aspects and the reusability. Two intermediate models are carried out in order to solve the complexity problem. The partitioning problem deals with the proposed hardware/software partitioning algorithm based on Ant Colony Optimisation. The reusability problem is resolved by synthesis of intellectual property blocks. Specification and integration of an intelligent controller on heterogeneous platform are considered to illustrate the proposed approach.展开更多
Hardware/software partitioning is an important step in the design of embedded systems. In this paper, the hardware/software partitioning problem is modeled as a constrained binary integer programming problem, which is...Hardware/software partitioning is an important step in the design of embedded systems. In this paper, the hardware/software partitioning problem is modeled as a constrained binary integer programming problem, which is further converted equivalently to an unconstrained binary integer programming problem by a penalty method. A local search method, HSFM, is developed to obtain a discrete local minimizer of the unconstrained binary integer programming problem. Next, an auxiliary function, which has the same global optimal solutions as the unconstrained binary integer programming problem, is constructed, and its properties are studied. We show that applying HSFM to minimize the auxiliary function can escape from previous local optima by the increase of the parameter value successfully. Finally, a discrete dynamic convexized method is developed to solve the hardware/software partitioning problem. Computational results and comparisons indicate that the proposed algorithm can get high-quality solutions.展开更多
A hardware/software co-synthesis method is presented for SoC designs consisting of both hardware IP cores and software components on a graph-theoretic formulation. Given a SoC integrated with a set of functions and a ...A hardware/software co-synthesis method is presented for SoC designs consisting of both hardware IP cores and software components on a graph-theoretic formulation. Given a SoC integrated with a set of functions and a set of performance factors, a core for each function is selected from a set of alternative IP cores and software components, and optimal partitions is found in a way to evenly balance the performance factors and to ultimately reduce the overall cost, size, power consumption and runtime of the core-based SoC. The algorithm formulates IP cores and components into the corresponding mathematical models, presents a graph-theoretic model for finding the optimal partitions of SoC design and transforms SoC hardware/software co-synthesis problem into finding optimal paths in a weighted, directed graph. Overcoming the three main deficiencies of the traditional methods, this method can work automatically, evaluate more performance factors at the same time and meet the particularity of SoC designs. At last, the approach is illustrated that is practical and effective through partitioning a practical system.展开更多
We present a simulation framework for wireless sensor networks developed to allow the design exploration and the complete microprocessor-instruction-level debug of network formation, data congestion, nodes interaction...We present a simulation framework for wireless sensor networks developed to allow the design exploration and the complete microprocessor-instruction-level debug of network formation, data congestion, nodes interaction, all in one simulation environment. A specifically innovative feature is the co-emulation of selected nodes at clock-cycle-accurate hardware processing level, allowing code debug and exact execution latency evaluation (considering both protocol stack and application), together with other nodes at abstract protocol level, meeting a designer’s needs of simulation speed, scalability and reliability. The simulator is centered on the Zigbee protocol and can be retargeted for different node micro-architectures.展开更多
Hardware/software partitioning is an essential step in hardware/software co-design.For large size problems,it is difficult to consider both solution quality and time.This paper presents an efficient GPU-based parallel...Hardware/software partitioning is an essential step in hardware/software co-design.For large size problems,it is difficult to consider both solution quality and time.This paper presents an efficient GPU-based parallel tabu search algorithm(GPTS)for HW/SW partitioning.A single GPU kernel of compacting neighborhood is proposed to reduce the amount of GPU global memory accesses theoretically.A kernel fusion strategy is further proposed to reduce the amount of GPU global memory accesses of GPTS.To further minimize the transfer overhead of GPTS between CPU and GPU,an optimized transfer strategy for GPU-based tabu evaluation is proposed,which considers that all the candidates do not satisfy the given constraint.Experiments show that GPTS outperforms state-of-the-art work of tabu search and is competitive with other methods for HW/SW partitioning.The proposed parallelization is significant when considering the ordinary GPU platform.展开更多
With the development of the design complexity in embedded systems, hardware/software （HW/SW） partitioning becomes a challenging optimization problem in HW/SW co-design. A novel HW/SW partitioning method based on pos...With the development of the design complexity in embedded systems, hardware/software （HW/SW） partitioning becomes a challenging optimization problem in HW/SW co-design. A novel HW/SW partitioning method based on position disturbed particle swarm optimization with invasive weed optimization （PDPSO-IWO） is presented in this paper. It is found by biologists that the ground squirrels produce alarm calls which warn their peers to move away when there is potential predatory threat. Here, we present PDPSO algorithm, in each iteration of which the squirrel behavior of escaping from the global worst particle can be simulated to increase population diversity and avoid local optimum. We also present new initialization and reproduction strategies to improve IWO algorithm for searching a better position, with which the global best position can be updated. Then the search accuracy and the solution quality can be enhanced. PDPSO and improved IWO are synthesized into one single PDPSO-IWO algorithm, which can keep both searching diversification and searching intensification. Furthermore, a hybrid NodeRank （HNodeRank） algorithm is proposed to initialize the population of PDPSO-IWO, and the solution quality can be enhanced further. Since the HW/SW communication cost computing is the most time-consuming process for HW/SW partitioning algorithm, we adopt the GPU parallel technique to accelerate the computing. In this way, the runtime of PDPSO-IWO for large-scale HW/SW partitioning problem can be reduced efficiently. Finally, multiple experiments on benchmarks from state-of-the-art publications and large-scale HW/SW partitioning demonstrate that the proposed algorithm can achieve higher performance than other algorithms.展开更多
This paper focuses on the algorithmic aspects for the hardware/software （HW/SW） partitioning which searches a reasonable composition of hardware and software components which not only satisfies the constraint of har...This paper focuses on the algorithmic aspects for the hardware/software （HW/SW） partitioning which searches a reasonable composition of hardware and software components which not only satisfies the constraint of hardware area but also optimizes the execution time. The computational model is extended so that all possible types of communications can be taken into account for the HW/SW partitioning. Also, a new dynamic programming algorithm is proposed on the basis of the computational model, in which source data, rather than speedup in previous work, of basic scheduling blocks are directly utilized to calculate the optimal solution. The proposed algorithm runs in O（n·A） for n code fragments and the available hardware area A. Simulation results show that the proposed algorithm solves the HW/SW partitioning without increase in running time, compared with the algorithm cited in the literature.展开更多
With the rapid development of artificial intelligence,the intelligence level of software is increasingly improving.Intelligent software,which is widely applied in crucial fields such as autonomous driving,intelligent ...With the rapid development of artificial intelligence,the intelligence level of software is increasingly improving.Intelligent software,which is widely applied in crucial fields such as autonomous driving,intelligent customer service,and medical diagnosis,is constructed based on complex technologies like machine learning and deep learning.Its uncertain behavior and data dependence pose unprecedented challenges to software testing.However,existing software testing courses mainly focus on conventional contents and are unable to meet the requirements of intelligent software testing.Therefore,this work deeply analyzed the relevant technologies of intelligent software testing,including reliability evaluation indicator system,neuron coverage,and test case generation.It also systematically designed an intelligent software testing course,covering teaching objectives,teaching content,teaching methods,and a teaching case.Verified by the practical teaching in four classes,this course has achieved remarkable results,providing practical experience for the reform of software testing courses.展开更多
In the context of large language model(LLM)reshaping software engineering education,this paper presents OSSerCopilot,a LLM-based tutoring system designed to address the critical challenge faced by newcomers(especially...In the context of large language model(LLM)reshaping software engineering education,this paper presents OSSerCopilot,a LLM-based tutoring system designed to address the critical challenge faced by newcomers(especially student contributors)in open source software(OSS)communities.Leveraging natural language processing,code semantic understanding,and learner profiling,the system functions as an intelligent tutor to scaffold three core competency domains:contribution guideline interpretation,project architecture comprehension,and personalized task matching.By transforming traditional onboarding barriers-such as complex contribution documentation and opaque project structures-into interactive learning journeys,OSSerCopilot enables newcomers to complete their first OSS contribution more easily and confidently.This paper highlights how LLM technologies can redefine software engineering education by bridging the gap between theoretical knowledge and practical OSS participation,offering implications for curriculum design,competency assessment,and sustainable OSS ecosystem cultivation.A demonstration video of the system is available at https://figshare.com/articles/media/OSSerCopilot_Introduction_mp4/29510276.展开更多
Heavy-ion collisions(HICs)is a unique experimental tool for investigating the properties of nuclear matter under extreme conditions in the laboratory.At HIRFL-CSR energies,HICs can create nuclear matter with 2-3 times...Heavy-ion collisions(HICs)is a unique experimental tool for investigating the properties of nuclear matter under extreme conditions in the laboratory.At HIRFL-CSR energies,HICs can create nuclear matter with 2-3 times the saturation density(ρ_(0)).The HIRFL-CSR external-target experiment(CEE)is a large-acceptance spectrometer designed to explore frontier topics in high-energy nuclear physics,such as the QCD phase structure and nuclear matter equation of states.In this letter,we introduce simulation and analysis software for the CEE experiment(CeeROOT).Based on the CEE conceptual design and CeeROOT software,the configurations of its subdetectors were optimized by considering foreseeable physical constraints.The final detector layout of the CEE spectrometer and its acceptances were validated through simulations of U+U collisions at 500 MeV/u and pp collisions at 2.8 GeV,which demonstrated that the CEE experiment will serve as a detector with wide acceptance and multi-particle identification capabilities for studying high-energy nuclear physics topics at HIRFL-CSR energies with pp,pA,and A A collisions.展开更多
While parametric Software Reliability Growth Models(SRGMs)serve as a cornerstone in software reliability assessment,their reliance on known fault-detection time distributions often presents a significant limitation in...While parametric Software Reliability Growth Models(SRGMs)serve as a cornerstone in software reliability assessment,their reliance on known fault-detection time distributions often presents a significant limitation in practical software testing.In this study,the authors develop a novel shaperestricted spline estimator for quantifying software reliability.Compared with parametric SRGMs,the proposed estimator not only shares a key characteristic with parametric SRGMs,but also obviates the need for specifying fault-detection time distributions.More importantly,it effectively utilizes the critical shape information of the mean value function(MVF)of fault-detection process,a detail seldom considered in prior work.Moreover,the authors investigate the predictive performance of the proposed methods by employing the so-called one-step look-ahead prediction method.Furthermore,the authors show that under certain conditions,the shape-restricted spline estimator will attain the point-wise convergence rate O_P(n~(-3/7)).In numerical experiment,the authors show that spline estimators under restriction demonstrate competitive performance compared to parametric and certain non-parametric models.展开更多
In the modern era of ubiquitous and highly interconnected information technology,cybersecurity threats stemming from software code vulnerabilities have become increasingly severe,posing significant risks to the confid...In the modern era of ubiquitous and highly interconnected information technology,cybersecurity threats stemming from software code vulnerabilities have become increasingly severe,posing significant risks to the confidentiality,integrity,and availability of modern information systems.To enhance software code quality,enterprises often integrate static code analysis tools into Continuous Integration(CI) pipelines.However,the high rates of false positives and false negatives remain a challenge.The advent of large language models(LLMs),such as ChatGPT,presents a new opportunity to address these challenges.In this paper,we propose AI-SCDF,a framework that utilizes the custombuilt Nebula-Coder AI model for detecting and fixing code security issues in real time during the developer ' s personal build process.We construct a static code checking rule knowledge base through summarizing and classifying Common Weakness Enumeration(CWE) code security problems identified by security and quality assurance teams.The rule knowledge base is combined with CodeFuse-processed code contexts to serve as input for an AI code security detection microservice,which assists in identifying code quality and security issues.If any abnormalities are detected,they are addressed by an AI code security patching microservice,which alerts the developer and requests confirmation before committing the code into the repository.Experimental results show that our approach effectively improves code quality.We also develop a VS Code plugin for code alert detection and fix based on LLMs,which facilitates test shift-left and lowers the risk of software development.展开更多
With the advent of the AI era,how can students effectively utilize generative AI large models to assist in course learning?At the same time,how can teachers utilize generative AI tools and the teaching concept of OBE ...With the advent of the AI era,how can students effectively utilize generative AI large models to assist in course learning?At the same time,how can teachers utilize generative AI tools and the teaching concept of OBE to stimulate students’innovative consciousness and teamwork ability,enabling students to identify some problems in a certain industry or field and creatively propose feasible solutions,and truly achieve the cultivation of new models in software engineering course teaching with the assistance of generative AI tools?This paper presents research and practice on a new model for cultivating software engineering courses that integrates generative AI and OBE,introduces the specific process of teaching reform and practice,and finally explains the achievements of teaching reform.展开更多
The rapid development of new-quality productive forces(NQPF)has intensified the demand for high-level innovative talent.As a representative of NQPF,generative artificial intelligence(GenAI)offers powerful tools to res...The rapid development of new-quality productive forces(NQPF)has intensified the demand for high-level innovative talent.As a representative of NQPF,generative artificial intelligence(GenAI)offers powerful tools to reshape talent cultivation but also presents significant challenges,including skill hollowing,ethical risks,and a growing disconnect between education and industry needs.Currently,graduate-level software engineering education struggles with outdated curricula and insufficient alignment with practical demands.In this paper,we propose a dual-core collaborative framework driven by“GenAI technology”and“industry demand”.Under this framework,we design a four-dimensional capability development path to enhance graduate students’innovation in software engineering practice.This path focuses on①scientific research innovation,②engineering problem-solving,③cross-domain collaborative evolution,and④ethical risk governance.The proposed approach promotes a shift from traditional knowledge transfer to human-machine collaborative innovation,aligning talent cultivation with the demands of the NQPF.展开更多
The rapid development of artificial intelligence(AI)has placed significant pressure on universities to rethink how they train software engineering students.Tools like GitHub Copilot can now generate basic code in seco...The rapid development of artificial intelligence(AI)has placed significant pressure on universities to rethink how they train software engineering students.Tools like GitHub Copilot can now generate basic code in seconds.This raises important questions:What is the value of traditional programming education?What role should instructors play when AI becomes a powerful teaching assistant?How should the goals of software engineering programs change as companies increasingly use AI to handle coding tasks?This paper explores the key challenges AI brings to software engineering education and proposes practical strategies for updating talent development models to meet these changes.展开更多
Small angle x-ray scattering(SAXS)is an advanced technique for characterizing the particle size distribution(PSD)of nanoparticles.However,the ill-posed nature of inverse problems in SAXS data analysis often reduces th...Small angle x-ray scattering(SAXS)is an advanced technique for characterizing the particle size distribution(PSD)of nanoparticles.However,the ill-posed nature of inverse problems in SAXS data analysis often reduces the accuracy of conventional methods.This article proposes a user-friendly software for PSD analysis,GranuSAS,which employs an algorithm that integrates truncated singular value decomposition(TSVD)with the Chahine method.This approach employs TSVD for data preprocessing,generating a set of initial solutions with noise suppression.A high-quality initial solution is subsequently selected via the L-curve method.This selected candidate solution is then iteratively refined by the Chahine algorithm,enforcing constraints such as non-negativity and improving physical interpretability.Most importantly,GranuSAS employs a parallel architecture that simultaneously yields inversion results from multiple shape models and,by evaluating the accuracy of each model's reconstructed scattering curve,offers a suggestion for model selection in material systems.To systematically validate the accuracy and efficiency of the software,verification was performed using both simulated and experimental datasets.The results demonstrate that the proposed software delivers both satisfactory accuracy and reliable computational efficiency.It provides an easy-to-use and reliable tool for researchers in materials science,helping them fully exploit the potential of SAXS in nanoparticle characterization.展开更多
文摘Ethernet over SDH/SONET (EOS) is a hotspot in today's data transmission technology for it combines the merits of both Ethernet and SDH/SONET. However, implementing an EOS system on a chip is complex and needs full verifications. This paper introduces our design of Hardware/Software co-verification platform for EOS design. The hardware platform contains a microprocessor board and an FPGA (Field Programmable Gate Array)-based verification board, and the corresponding software includes test benches running in FPGAs, controlling programs for the microprocessor and a console program with GUI (Graphical User Interface) interface for configuration, management and supervision. The design is cost-effective and has been successfully employed to verify several IP (Intellectual Property) blocks of our EOS chip. Moreover, it is flexible and can be applied as a general-purpose verification platform.
基金Supported by the National Natural Science Foundation of China(No.61179045 and No.61350009)
文摘In this paper, the storage capacity of communication among cores and processors is taken into account and a maximum D-value-first algorithm is proposed. By improving the hardware parallelism in the task execution process, the maximum storage requirements for communication are minimized. Experimental results with various directed acyclic graph models showed that compared with the earliest-task-first algorithm, the storage requirements for communication were reduced by 22.46%, on average, while the average of makespan only increased by 0.82%,.
基金Sponsored by the Natural Science Foundation of Heilongjiang Province( Grant No B2007-07)Industrial Research Projects in Qiqihaer( Grant No GYGG-09009)
文摘This paper presents an algorithm that combines the chaos optimization algorithm with the maximum entropy ( COA-ME) by using entropy model based on chaos algorithm,in which the maximum entropy is used as the second method of searching the excellent solution. The search direction is improved by chaos optimization algorithm and realizes the selective acceptance of wrong solution. The experimental result shows that the presented algorithm can be used in the partitioning of hardware/software of reconfigurable system. It effectively reduces the local extremum problem,and search speed as well as performance of partitioning is improved.
基金Project supported by the Key-Tech Program of Zhejiang Province,China (No. 021101559), and the Fok Ying Tong Education Founda-tion (No. 94031), China
文摘In order to improve the efficiency of embedded software running on processor core, this paper proposes a hard-ware/software co-optimization approach for embedded software from the system point of view. The proposed stepwise methods aim at exploiting the structure and the resources of the processor as much as possible for software algorithm optimization. To achieve low memory usage and low frequency need for the same performance, this co-optimization approach was used to optimize embedded software of MP3 decoder based on a 16-bit fixed-point DSP core. After the optimization, the results of decoding 128 kbps, 44.1 kHz stereo MP3 on DSP evaluation platform need 45.9 MIPS and 20.4 kbytes memory space. The optimization rate achieves 65.6% for memory and 49.6% for frequency respectively compared with the results by compiler using floating-point computation. The experimental result indicates the availability of the hardware/software co-optimization approach depending on the algorithm and architecture.
文摘This paper deals with a new hardware/software embedded system design methodology based on design pattern approach by development of a new design tool called smartcell. Three main constraints of embedded systems design process are investigated: the complexity, the partitioning between hardware and software aspects and the reusability. Two intermediate models are carried out in order to solve the complexity problem. The partitioning problem deals with the proposed hardware/software partitioning algorithm based on Ant Colony Optimisation. The reusability problem is resolved by synthesis of intellectual property blocks. Specification and integration of an intelligent controller on heterogeneous platform are considered to illustrate the proposed approach.
基金Supported by the National Natural Science Foundation of China(11301255)the Fund by Collaborative Innovation Center of IoT Industrialization and Intelligent Production,Minjiang University(IIC1703)+1 种基金Foundation of Minjiang University(MYK17032)the Program for New Century Excellent Talents in Fujian Province University
文摘Hardware/software partitioning is an important step in the design of embedded systems. In this paper, the hardware/software partitioning problem is modeled as a constrained binary integer programming problem, which is further converted equivalently to an unconstrained binary integer programming problem by a penalty method. A local search method, HSFM, is developed to obtain a discrete local minimizer of the unconstrained binary integer programming problem. Next, an auxiliary function, which has the same global optimal solutions as the unconstrained binary integer programming problem, is constructed, and its properties are studied. We show that applying HSFM to minimize the auxiliary function can escape from previous local optima by the increase of the parameter value successfully. Finally, a discrete dynamic convexized method is developed to solve the hardware/software partitioning problem. Computational results and comparisons indicate that the proposed algorithm can get high-quality solutions.
基金This project was supported by the Defense Pre-Research Project of the ‘Tenth Five-Year-Plan’ of China(41315040106) and the National"863"High Technology Research and Development Programof China (2003AAIZ2210)
文摘A hardware/software co-synthesis method is presented for SoC designs consisting of both hardware IP cores and software components on a graph-theoretic formulation. Given a SoC integrated with a set of functions and a set of performance factors, a core for each function is selected from a set of alternative IP cores and software components, and optimal partitions is found in a way to evenly balance the performance factors and to ultimately reduce the overall cost, size, power consumption and runtime of the core-based SoC. The algorithm formulates IP cores and components into the corresponding mathematical models, presents a graph-theoretic model for finding the optimal partitions of SoC design and transforms SoC hardware/software co-synthesis problem into finding optimal paths in a weighted, directed graph. Overcoming the three main deficiencies of the traditional methods, this method can work automatically, evaluate more performance factors at the same time and meet the particularity of SoC designs. At last, the approach is illustrated that is practical and effective through partitioning a practical system.
文摘We present a simulation framework for wireless sensor networks developed to allow the design exploration and the complete microprocessor-instruction-level debug of network formation, data congestion, nodes interaction, all in one simulation environment. A specifically innovative feature is the co-emulation of selected nodes at clock-cycle-accurate hardware processing level, allowing code debug and exact execution latency evaluation (considering both protocol stack and application), together with other nodes at abstract protocol level, meeting a designer’s needs of simulation speed, scalability and reliability. The simulator is centered on the Zigbee protocol and can be retargeted for different node micro-architectures.
基金This paper was supported by the National Natural Science Foundation of China(Grant No.61472289)National Key Research and Development Project(2016YFC0106305).We also would like to thank the anonymous reviewers for their valuable and constructive comments.
文摘Hardware/software partitioning is an essential step in hardware/software co-design.For large size problems,it is difficult to consider both solution quality and time.This paper presents an efficient GPU-based parallel tabu search algorithm(GPTS)for HW/SW partitioning.A single GPU kernel of compacting neighborhood is proposed to reduce the amount of GPU global memory accesses theoretically.A kernel fusion strategy is further proposed to reduce the amount of GPU global memory accesses of GPTS.To further minimize the transfer overhead of GPTS between CPU and GPU,an optimized transfer strategy for GPU-based tabu evaluation is proposed,which considers that all the candidates do not satisfy the given constraint.Experiments show that GPTS outperforms state-of-the-art work of tabu search and is competitive with other methods for HW/SW partitioning.The proposed parallelization is significant when considering the ordinary GPU platform.
基金The work was supported by the National Natural Science Foundation of China under Grant No. 61472289 and the National Key Research and Development Project of China under Grant No. 2016YFC0106305.
文摘With the development of the design complexity in embedded systems, hardware/software （HW/SW） partitioning becomes a challenging optimization problem in HW/SW co-design. A novel HW/SW partitioning method based on position disturbed particle swarm optimization with invasive weed optimization （PDPSO-IWO） is presented in this paper. It is found by biologists that the ground squirrels produce alarm calls which warn their peers to move away when there is potential predatory threat. Here, we present PDPSO algorithm, in each iteration of which the squirrel behavior of escaping from the global worst particle can be simulated to increase population diversity and avoid local optimum. We also present new initialization and reproduction strategies to improve IWO algorithm for searching a better position, with which the global best position can be updated. Then the search accuracy and the solution quality can be enhanced. PDPSO and improved IWO are synthesized into one single PDPSO-IWO algorithm, which can keep both searching diversification and searching intensification. Furthermore, a hybrid NodeRank （HNodeRank） algorithm is proposed to initialize the population of PDPSO-IWO, and the solution quality can be enhanced further. Since the HW/SW communication cost computing is the most time-consuming process for HW/SW partitioning algorithm, we adopt the GPU parallel technique to accelerate the computing. In this way, the runtime of PDPSO-IWO for large-scale HW/SW partitioning problem can be reduced efficiently. Finally, multiple experiments on benchmarks from state-of-the-art publications and large-scale HW/SW partitioning demonstrate that the proposed algorithm can achieve higher performance than other algorithms.
文摘This paper focuses on the algorithmic aspects for the hardware/software （HW/SW） partitioning which searches a reasonable composition of hardware and software components which not only satisfies the constraint of hardware area but also optimizes the execution time. The computational model is extended so that all possible types of communications can be taken into account for the HW/SW partitioning. Also, a new dynamic programming algorithm is proposed on the basis of the computational model, in which source data, rather than speedup in previous work, of basic scheduling blocks are directly utilized to calculate the optimal solution. The proposed algorithm runs in O（n·A） for n code fragments and the available hardware area A. Simulation results show that the proposed algorithm solves the HW/SW partitioning without increase in running time, compared with the algorithm cited in the literature.
基金Computer Basic Education Teaching Research Project of Association of Fundamental Computing Education in Chinese Universities(Nos.2025-AFCEC-527 and 2024-AFCEC-088)Research on the Reform of Public Course Teaching at Nantong College of Science and Technology(No.2024JGG015).
文摘With the rapid development of artificial intelligence,the intelligence level of software is increasingly improving.Intelligent software,which is widely applied in crucial fields such as autonomous driving,intelligent customer service,and medical diagnosis,is constructed based on complex technologies like machine learning and deep learning.Its uncertain behavior and data dependence pose unprecedented challenges to software testing.However,existing software testing courses mainly focus on conventional contents and are unable to meet the requirements of intelligent software testing.Therefore,this work deeply analyzed the relevant technologies of intelligent software testing,including reliability evaluation indicator system,neuron coverage,and test case generation.It also systematically designed an intelligent software testing course,covering teaching objectives,teaching content,teaching methods,and a teaching case.Verified by the practical teaching in four classes,this course has achieved remarkable results,providing practical experience for the reform of software testing courses.
基金supported by the National Natural Science Foundation of China (62202022, 92582204, and 62572030)the Fundamental Research Funds for the Central Universitiesthe exploratory elective projects of the State Key Laboratory of Complex and Critical Software Environments
文摘In the context of large language model(LLM)reshaping software engineering education,this paper presents OSSerCopilot,a LLM-based tutoring system designed to address the critical challenge faced by newcomers(especially student contributors)in open source software(OSS)communities.Leveraging natural language processing,code semantic understanding,and learner profiling,the system functions as an intelligent tutor to scaffold three core competency domains:contribution guideline interpretation,project architecture comprehension,and personalized task matching.By transforming traditional onboarding barriers-such as complex contribution documentation and opaque project structures-into interactive learning journeys,OSSerCopilot enables newcomers to complete their first OSS contribution more easily and confidently.This paper highlights how LLM technologies can redefine software engineering education by bridging the gap between theoretical knowledge and practical OSS participation,offering implications for curriculum design,competency assessment,and sustainable OSS ecosystem cultivation.A demonstration video of the system is available at https://figshare.com/articles/media/OSSerCopilot_Introduction_mp4/29510276.
基金supported by the Strategic Priority Research Program of Chinese Academy of Sciences(No.XDB34030000)the National Natural Science Foundation of China(Nos.11927901 and 12475133)+1 种基金the Youth Team Program in Basic Research Fields Stably Supported by the Chinese Academy of Sciences(No.YSBR-088)the Western Light Project of the Chinese Academy of Sciences。
文摘Heavy-ion collisions(HICs)is a unique experimental tool for investigating the properties of nuclear matter under extreme conditions in the laboratory.At HIRFL-CSR energies,HICs can create nuclear matter with 2-3 times the saturation density(ρ_(0)).The HIRFL-CSR external-target experiment(CEE)is a large-acceptance spectrometer designed to explore frontier topics in high-energy nuclear physics,such as the QCD phase structure and nuclear matter equation of states.In this letter,we introduce simulation and analysis software for the CEE experiment(CeeROOT).Based on the CEE conceptual design and CeeROOT software,the configurations of its subdetectors were optimized by considering foreseeable physical constraints.The final detector layout of the CEE spectrometer and its acceptances were validated through simulations of U+U collisions at 500 MeV/u and pp collisions at 2.8 GeV,which demonstrated that the CEE experiment will serve as a detector with wide acceptance and multi-particle identification capabilities for studying high-energy nuclear physics topics at HIRFL-CSR energies with pp,pA,and A A collisions.
文摘While parametric Software Reliability Growth Models(SRGMs)serve as a cornerstone in software reliability assessment,their reliance on known fault-detection time distributions often presents a significant limitation in practical software testing.In this study,the authors develop a novel shaperestricted spline estimator for quantifying software reliability.Compared with parametric SRGMs,the proposed estimator not only shares a key characteristic with parametric SRGMs,but also obviates the need for specifying fault-detection time distributions.More importantly,it effectively utilizes the critical shape information of the mean value function(MVF)of fault-detection process,a detail seldom considered in prior work.Moreover,the authors investigate the predictive performance of the proposed methods by employing the so-called one-step look-ahead prediction method.Furthermore,the authors show that under certain conditions,the shape-restricted spline estimator will attain the point-wise convergence rate O_P(n~(-3/7)).In numerical experiment,the authors show that spline estimators under restriction demonstrate competitive performance compared to parametric and certain non-parametric models.
文摘In the modern era of ubiquitous and highly interconnected information technology,cybersecurity threats stemming from software code vulnerabilities have become increasingly severe,posing significant risks to the confidentiality,integrity,and availability of modern information systems.To enhance software code quality,enterprises often integrate static code analysis tools into Continuous Integration(CI) pipelines.However,the high rates of false positives and false negatives remain a challenge.The advent of large language models(LLMs),such as ChatGPT,presents a new opportunity to address these challenges.In this paper,we propose AI-SCDF,a framework that utilizes the custombuilt Nebula-Coder AI model for detecting and fixing code security issues in real time during the developer ' s personal build process.We construct a static code checking rule knowledge base through summarizing and classifying Common Weakness Enumeration(CWE) code security problems identified by security and quality assurance teams.The rule knowledge base is combined with CodeFuse-processed code contexts to serve as input for an AI code security detection microservice,which assists in identifying code quality and security issues.If any abnormalities are detected,they are addressed by an AI code security patching microservice,which alerts the developer and requests confirmation before committing the code into the repository.Experimental results show that our approach effectively improves code quality.We also develop a VS Code plugin for code alert detection and fix based on LLMs,which facilitates test shift-left and lowers the risk of software development.
基金supported by the Shanghai Municipal Education Research Project“Exploring the Practical Application of Generative Artificial Intelligence in Cultivating Innovative Thinking and Capabilities of Interdisciplinary Application Technology Talents‘Practice Path’”(C2025299)the university-level postgraduate course project“Software Process Management”(PX-2025251502)of Shanghai Sanda Universitythe key course project at the university level of Shanghai Sanda University,“Introduction to Software Engineering”(PX-5241216).
文摘With the advent of the AI era,how can students effectively utilize generative AI large models to assist in course learning?At the same time,how can teachers utilize generative AI tools and the teaching concept of OBE to stimulate students’innovative consciousness and teamwork ability,enabling students to identify some problems in a certain industry or field and creatively propose feasible solutions,and truly achieve the cultivation of new models in software engineering course teaching with the assistance of generative AI tools?This paper presents research and practice on a new model for cultivating software engineering courses that integrates generative AI and OBE,introduces the specific process of teaching reform and practice,and finally explains the achievements of teaching reform.
基金supported in part by the Graduate Education Reform Research Project of Hubei University of Technology under Grant 2024YB003the Hubei University of Arts and Science,Teaching Research Project,under Grant JY2025018.
文摘The rapid development of new-quality productive forces(NQPF)has intensified the demand for high-level innovative talent.As a representative of NQPF,generative artificial intelligence(GenAI)offers powerful tools to reshape talent cultivation but also presents significant challenges,including skill hollowing,ethical risks,and a growing disconnect between education and industry needs.Currently,graduate-level software engineering education struggles with outdated curricula and insufficient alignment with practical demands.In this paper,we propose a dual-core collaborative framework driven by“GenAI technology”and“industry demand”.Under this framework,we design a four-dimensional capability development path to enhance graduate students’innovation in software engineering practice.This path focuses on①scientific research innovation,②engineering problem-solving,③cross-domain collaborative evolution,and④ethical risk governance.The proposed approach promotes a shift from traditional knowledge transfer to human-machine collaborative innovation,aligning talent cultivation with the demands of the NQPF.
基金supported in part by the Northeastern University’s 2024 Undergraduate Education and Teaching Reform Research Project:Innovation and Practice of Professional Course Teaching Paradigms in the Context of Digital Education.
文摘The rapid development of artificial intelligence(AI)has placed significant pressure on universities to rethink how they train software engineering students.Tools like GitHub Copilot can now generate basic code in seconds.This raises important questions:What is the value of traditional programming education?What role should instructors play when AI becomes a powerful teaching assistant?How should the goals of software engineering programs change as companies increasingly use AI to handle coding tasks?This paper explores the key challenges AI brings to software engineering education and proposes practical strategies for updating talent development models to meet these changes.
基金Project supported by the Project of the Anhui Provincial Natural Science Foundation(Grant No.2308085MA19)Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA0410401)+2 种基金the National Natural Science Foundation of China(Grant No.52202120)the National Key Research and Development Program of China(Grant No.2023YFA1609800)USTC Research Funds of the Double First-Class Initiative(Grant No.YD2310002013)。
文摘Small angle x-ray scattering(SAXS)is an advanced technique for characterizing the particle size distribution(PSD)of nanoparticles.However,the ill-posed nature of inverse problems in SAXS data analysis often reduces the accuracy of conventional methods.This article proposes a user-friendly software for PSD analysis,GranuSAS,which employs an algorithm that integrates truncated singular value decomposition(TSVD)with the Chahine method.This approach employs TSVD for data preprocessing,generating a set of initial solutions with noise suppression.A high-quality initial solution is subsequently selected via the L-curve method.This selected candidate solution is then iteratively refined by the Chahine algorithm,enforcing constraints such as non-negativity and improving physical interpretability.Most importantly,GranuSAS employs a parallel architecture that simultaneously yields inversion results from multiple shape models and,by evaluating the accuracy of each model's reconstructed scattering curve,offers a suggestion for model selection in material systems.To systematically validate the accuracy and efficiency of the software,verification was performed using both simulated and experimental datasets.The results demonstrate that the proposed software delivers both satisfactory accuracy and reliable computational efficiency.It provides an easy-to-use and reliable tool for researchers in materials science,helping them fully exploit the potential of SAXS in nanoparticle characterization.
