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Towards optimized tensor code generation for deep learning on sunway many-core processor

Frontiers of computer Science 2024年第2期18卷 1-15页

作者： Mingzhen LI Changxi LIU Jianjin LIAO Xuegui ZHENG Hailong YANG Rujun SUN Jun XU Lin GAN Guangwen YANG Zhongzhi LUAN Depei QIAN State Key Laboratory of Software Development Environment Beijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China National University of Singapore Singapore 119077Singapore State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214000China Science and Technology on Special System Simulation Laboratory Beijing Simulation Center Beijing 100854China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China

The flourish of deep learning frameworks and hardware platforms has been demanding an efficient compiler that can shield the diversity in both software and hardware in order to provide application *** the existing deep learning compilers,TVM is well known for its efficiency in code generation and optimization across diverse hardware *** the meanwhile,the Sunway many-core processor renders itself as a competitive candidate for its attractive computational power in both scientific computing and deep learning *** paper combines the trends in these two ***,we propose swTVM that extends the original TVM to support ahead-of-time compilation for architecture requiring cross-compilation such as *** addition,we leverage the architecture features during the compilation such as core group for massive parallelism,DMA for high bandwidth memory transfer and local device memory for data locality,in order to generate efficient codes for deep learning workloads on *** experiment results show that the codes generated by swTVM achieve 1.79x improvement of inference latency on average compared to the state-of-the-art deep learning framework on Sunway,across eight representative *** work is the first attempt from the compiler perspective to bridge the gap of deep learning and Sunway processor particularly with productivity and efficiency in *** believe this work will encourage more people to embrace the power of deep learning and Sunwaymany-coreprocessor.

关键词： sunway processor deep learning compiler code generation performance optimization

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Object Oriented BDD and Executable Human-Language Module Specification 26

Object Oriented BDD and Executable Human-Language Module Spe...

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26th ACIS International Winter Conference on software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD-Winter 2023

作者： Lee, Eric Gong, Jiayu Cao, Qinghong Intelligent Technology Co. Ltd. Shanghai China Shanghai Key Laboratory of Computer Software Testing & Evaluation Shanghai Development Center of Computer Software Technology Shanghai China System Operation Department Shanghai Stock Exchange Shanghai China

ISBN: (纸本)9798350345865

This paper presents an approach to software development which uses a generative AI Model as compiler to translate human language requirements into high-level programming language. We propose an executable human-language module specification and a tool to support it, which has been used successfully for human-language UI test automation. We anticipate further development of this approach to enable complex software to be programmed in human language, allowing for more intuitive and efficient software development. © 2023 IEEE.

关键词： Specifications

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Honeytoken-Detector: A Symbolic Execution-Based Honeypot Token Detection Tool 26

Honeytoken-Detector: A Symbolic Execution-Based Honeypot Tok...

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26th ACIS International Winter Conference on software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD-Winter 2023

作者： Liu, Yi Cai, Lizhi School of Information Science and Engineering East China University of Science and Technology Shanghai China Shanghai Development Center of Computer Software Technology Shanghai Key Laboratory of Computer Testing & Evaluating Shanghai China

ISBN: (纸本)9798350345865

Smart contracts have emerged as one of the most successful applications in the blockchain domain, playing a significant role in various blockchain ecosystems. Inspired by smart contracts, a multitude of cryptographic assets have been created. To standardize these assets, industry standards such as ERC20 (Ethereum Request for Comments 20), ERC721, and ERC1155 have been proposed. In recent years, smart contracts have frequently fallen victim to attacks. Honeypot contracts, disguised as ERC20-compliant tokens, are widely prevalent on the blockchain, enticing victims to make purchases. Such malicious smart contracts exhibiting deceptive behavior are collectively referred to as honeypot tokens. This paper focuses on ERC20-compliant smart contracts and defines six common types of honeypot issues. Building upon advancements in smart contract vulnerability detection, we propose an enhanced symbolic execution-based detection tool called Honeytoken-Detector. We conduct experiments on both contracts known to have similar issues and actual token contracts from the real world. The experimental results demonstrate the effectiveness of our tool in identifying vulnerabilities. © 2023 IEEE.

关键词： Smart contract

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Automated Functionality and Security Evaluation of Large Language Models

Automated Functionality and Security Evaluation of Large Lan...

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IEEE International Conference on Smart Cloud (SmartCloud)

作者： Minjie Ding Ying Shen Mingang Chen Shanghai Key Laboratory of Computer Software Testing and Evaluating Shanghai Development Center of Computer Software Technology Shanghai China

ISBN: (数字)9798350389500

ISBN: (纸本)9798350389517

Natural language processing (NLP) is rapidly developing. A series of Large Language Models (LLMs) have emerged, represented by ChatGPT, which have made significant breakthroughs in natural language understanding and generation, enabling fluent dialogue with humans, understanding human intentions, and completing complex tasks. However, in addition to the fairness and toxicity of traditional language models, some new problems, including hallucination, have also emerged in LLMs, making them hard to use. Evaluating LLMs manually is challenging due to subjectivity and inefficiency. In this paper, we focused on the fuzzy matching, toxicity detection, and hallucination detection in the evaluation of LLMs automatically, and fine-tune the Mixtral-8x7B Model, which can be deployed in private cloud environment, and prove the effectiveness of our method through experiments.

关键词： Cloud computing Toxicology Accuracy Graphics processing units Chatbots Security Task analysis

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IVIFUZZER: A Fuzzing method for vulnerability exploitation on the operating interface of the In-Vehicle Infotainment system

IVIFUZZER: A Fuzzing method for vulnerability exploitation o...

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Artificial Intelligence, Networking and Information technology (AINIT), International Seminar on

作者： Jianhua Wu Xin Zhang Shanghai Key Laboratory of Computer Software Testing and Evaluating Shanghai Development Center of Computer Software Technology Shanghai China

ISBN: (数字)9798350385557

ISBN: (纸本)9798350385564

As an important information system of intelligent and connected vehicles, most In-Vehicle Infotainment systems are set up and manage the vehicles through user interaction. This paper presents a Fuzzing method IVIFUZZER for vulnerability exploitation on the operation interface of the In-Vehicle Infotainment system. With the help of automated robotic arm and improved OCR technology, collecting system leakage information and directional detection of the identified input points, 6 zero day vulnerabilities were found. The experimental results show that the proposed IVIFUZZER method is effective.

关键词： Seminars Industries Optical character recognition Passwords Fuzzing Manipulators Information leakage

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An Evaluation System for Large Language Models based on Open-Ended Questions

An Evaluation System for Large Language Models based on Open...

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IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)

作者： Zhiyuan Cao Zeyu Ma Mingang Chen Computer and Information Engineering College Shanghai Polytechnic University Shanghai Key Laboratory of Computer Software Testing and Evaluating Shanghai Development Center of Computer software Technology Shanghai China Shanghai Key Laboratory of Computer Software Testing and Evaluating Shanghai Development Center of Computer software Technology Mathematical and Science College Shanghai Normal University Shanghai China Shanghai Key Laboratory of Computer Software Testing and Evaluating Shanghai Development Center of Computer software Technology Shanghai China

ISBN: (数字)9798350376982

ISBN: (纸本)9798350376999

We designed a large language model evaluation system based on open-ended questions. The system accomplished multidimensional evaluation of LLMs using open-ended questions, and it presented evaluation results with evaluation reports. Currently, the evaluation of large-scale language models often exists with two prominent limitations: (1) The evaluation methods are often single-minded, resulting in less credible results. (2) Most evaluations are based on datasets with closed-ended questions, treating generative large language models as discriminative models, which fails to adequately reflect the high output flexibility characteristic of these models. For these two limitations, we proposed an evaluation system for LLMs based on open-ended questions. Our experiments on the adapted open-source datasets demonstrated the effectiveness of this system. The code of the system was released on https://***/JerryMazeyu/GreatLibrarian.

关键词： Adaptation models Cloud computing Accuracy Codes Large language models System performance Reflection

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Multi-Objective Optimization of Multi-Product Parallel Disassembly Line Balancing Problem Considering Multi-Skilled Workers Using a Discrete Chemical Reaction Optimization Algorithm

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computers, Materials & Continua 2024年第9期80卷 4475-4496页

作者： Xiwang Guo Liangbo Zhou Zhiwei Zhang Liang Qi Jiacun Wang Shujin Qin Jinrui Cao College of Information and Control Engineering Liaoning Petrochemical UniversityFushun113000China Department of Computer Science and Technology Shandong University of Science and TechnologyQingdao266590China Department of Computer Science and Software Engineering Monmouth UniversityWest Long BranchNJ 07764USA Research Center of the Economic and Social Development of Henan East Provincial Joint Shangqiu Normal UniversityShangqiu476000China Department of Computer Science New Jersey City UniversityJersey CityNJ 07305USA

This work investigates a multi-product parallel disassembly line balancing problem considering multi-skilled workers.A mathematical model for the parallel disassembly line is established to achieve maximized disassembly profit and minimized workstation cycle *** on a product’s AND/OR graph,matrices for task-skill,worker-skill,precedence relationships,and disassembly correlations are developed.A multi-objective discrete chemical reaction optimization algorithm is *** enhance solution diversity,improvements are made to four reactions:decomposition,synthesis,intermolecular ineffective collision,and wall invalid collision reaction,completing the evolution of molecular *** established model and improved algorithm are applied to ball pen,flashlight,washing machine,and radio combinations,*** a Collaborative Resource Allocation(CRA)strategy based on a Decomposition-Based Multi-Objective Evolutionary Algorithm,the experimental results are compared with four classical algorithms:MOEA/D,MOEAD-CRA,Non-dominated Sorting Genetic Algorithm Ⅱ(NSGA-Ⅱ),and Non-dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ).This validates the feasibility and superiority of the proposed algorithm in parallel disassembly production lines.

关键词： Parallel disassembly line balancing problem multi-product multiskilled workers discrete chemical reaction optimization algorithm

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Research on key technologies of edge cache in virtual data space across WAN

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Frontiers of computer Science 2023年第1期17卷 15-34页

作者： Jiantong HUO Yaowen XU Zhisheng HUO Limin XIAO Zhenxue HE State Key Laboratory of Software Development Environment Beihang UniversityBeijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China High Performance Computing Center Beihang UniversityBeijing 100191China College of Software Beihang UniversityBeijing 100191China Hebei Key Laboratory of Agricultural Big Data Hebei Agricultural UniversityBaoding 071001China College of Computer Science and Technology Zhejiang UniversityHangZhou 310013China

The authors of this paper have previously proposed the global virtual data space system (GVDS) to aggregate the scattered and autonomous storage resources in China’s national supercomputer grid (National Supercomputing center in Guangzhou, National Supercomputing center in Jinan, National Supercomputing center in Changsha, Shanghai Supercomputing center, and computer Network Information center in Chinese Academy of Sciences) into a storage system that spans the wide area network (WAN), which realizes the unified management of global storage resources in China. At present, the GVDS has been successfully deployed in the China National Grid environment. However, when accessing and sharing remote data in the WAN, the GVDS will cause redundant transmission of data and waste a lot of network bandwidth resources. In this paper, we propose an edge cache system as a supplementary system of the GVDS to improve the performance of upper-level applications accessing and sharing remote data. Specifically, we first designs the architecture of the edge cache system, and then study the key technologies of this architecture: the edge cache index mechanism based on double-layer hashing, the edge cache replacement strategy based on the GDSF algorithm, the request routing based on consistent hashing method, and the cluster member maintenance method based on the SWIM protocol. The experimental results show that the edge cache system has successfully implemented the relevant operation functions (read, write, deletion, modification, etc.) and is compatible with the POSIX interface in terms of function. Further, it can greatly reduce the amount of data transmission and increase the data access bandwidth when the accessed file is located at the edge cache system in terms of performance, i.e., its performance is close to the performance of the network file system in the local area network (LAN).

关键词： virtual data space system wide area network edge cache redundant data transmission

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UniM-OV3D: Uni-Modality Open-Vocabulary 3D Scene Understanding with Fine-Grained Feature Representation

arXiv

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arXiv 2024年

作者： He, Qingdong Peng, Jinlong Jiang, Zhengkai Wu, Kai Ji, Xiaozhong Zhang, Jiangning Wang, Yabiao Wang, Chengjie Chen, Mingang Wu, Yunsheng YouTu Lab Tencent China Shanghai Development Center of Computer Software Technology China

3D open-vocabulary scene understanding aims to recognize arbitrary novel categories beyond the base label space. However, existing works not only fail to fully utilize all the available modal information in the 3D domain but also lack sufficient granularity in representing the features of each modality. In this paper, we propose a unified multimodal 3D open-vocabulary scene understanding network, namely UniM-OV3D, which aligns point clouds with image, language and depth. To better integrate global and local features of the point clouds, we design a hierarchical point cloud feature extraction module that learns comprehensive fine-grained feature representations. Further, to facilitate the learning of coarse-to-fine point-semantic representations from captions, we propose the utilization of hierarchical 3D caption pairs, capitalizing on geometric constraints across various viewpoints of 3D scenes. Extensive experimental results demonstrate the effectiveness and superiority of our method in open-vocabulary semantic and instance segmentation, which achieves state-of-the-art performance on both indoor and outdoor benchmarks such as ScanNet, ScanNet200, S3IDS and nuScenes. Code is available at https://***/hithqd/UniM-OV3D. Copyright © 2024, The Authors. All rights reserved.

关键词： Semantics

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GUNGNIR: EXPLOITING STYLISTIC FEATURES IN IMAGES FOR BACKDOOR ATTACKS ON DIFFUSION MODELS

arXiv

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arXiv 2025年

作者： Pan, Yu Dai, Bingrong Chen, Jiahao Wang, Lin Du, Yi Liu, Jiao School of Computer and Information Engineering Shanghai Polytechnic University China Shanghai Development Center of Computer Software Technology China

In recent years, Diffusion Models (DMs) have demonstrated significant advances in the field of image generation. However, according to current research, DMs are vulnerable to backdoor attacks, which allow attackers to control the model’s output by inputting data containing covert triggers, such as a specific patch or phrase. Existing defense strategies are well equipped to thwart such attacks through backdoor detection and trigger inversion because previous attack methods are constrained by limited input spaces and triggers defined by low-dimensional features. To bridge these gaps, we propose Gungnir, a novel method that enables attackers to activate the backdoor in DMs through hidden style triggers within input images. Our approach proposes using stylistic features as triggers for the first time and implements backdoor attacks successfully in image2image tasks by utilizing Reconstructing-Adversarial Noise (RAN) and Short-Term-Timesteps-Retention (STTR) of DMs. Meanwhile, experiments demonstrate that our method can easily bypass existing defense methods. Among existing DM main backdoor defense frameworks, our approach achieves a 0% backdoor detection rate (BDR). Our codes are available at https://***/paoche11/Gungnir. © 2025, CC BY.

关键词： HTTP

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