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Exploring high-performance processor architecture beyond the exascale

Frontiers of Information Technology & Electronic engineering 2018年第10期19卷 1224-1229页

作者： Xiang-hui XIE Xun JIA State Key Laboratory of Mathematical Engineering and Advanced Computing

The ever-increasing need for high performance in scientific computation and engineering applications will push high-perfornlance computing beyond the exascale. As an integral part of a supercomputing system, high- performance processors and their architecture designs are crucial in improving system performance. In this paper, three architecture design goals for high-performance processors beyond the *** are introduced, including effective performance scaling, efficient resource utilization, and adaptation to diverse applications. Then a high-performance many-core processor architecture with scalar processing and application-specific acceleration （Massa） is proposed, which aims to achieve the above three goals by employing the techniques of distributed computational resources and application-customized hardware. Finally, some future research directions regarding the Massa architecture are discussed.

关键词： High-performance computing Beyond the exascale Processor architecture Application-customized hardware Distributed computational resources

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Vulnerability model and attack path prediction of the UEFI firmware platform based on risk propagation 11

Vulnerability model and attack path prediction of the UEFI f...

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2021 11th International Workshop on Computer Science and engineering, WCSE 2021

作者： Jiao, Weihua Li, Qingbao Chen, Zhifeng Cao, Fei State Key Laboratory of Mathematical Engineering and Advanced Computing China

ISBN: (纸本)9789811817915

Targeted at the situation of rampant attack on UEFI Platform Firmware, this paper systematically analyzes the Security mechanisms of UEFI platform firmware. Then the vulnerability factors of UEFI firmware are described by modeling language, and a vulnerability model of UEFI firmware platform based on risk propagation (VMURP) is proposed. This paper introduces an improved PageRank algorithm to this model to reduce the influence of subjective factors which influences the accuracy of model. Based on VMURP model, an innovative method is proposed which using security configuration vector and attack vector to evaluate attack paths. Then, we use this method and VMURP to predict the most possible attack path of specific UEFI firmware platform. Finally, verify the rationality of the model and the validity of the prediction by experimental analysis. This study is helpful to quickly evaluate the vulnerability of UEFI firmware platform and predict possible attacks, gives platform managers more targeted guidance and suggestions to strengthen the security mechanisms. © 2021 11th International Workshop on Computer Science and engineering, WCSE 2021. All Rights Reserved.

关键词： Forecasting

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2020 International Conference on Computer Vision, Image and Deep Learning, CVIDL 2020

作者： Sun, Wenjie Shan, Zheng Liu, Fudong Qiao, Meng Gui, Hairen Li, Xingwei State Key Laboratory of Mathematical Engineering and Advanced Computing China

ISBN: (数字)9781728194813

ISBN: (纸本)9781728194813

Graph matching has a wide range of applications. However, graph matching faces two challenges: high computational complexity and loss information of graph embedded. In order to solve these two problems and correctly identify the similarity between two function control flow graphs, we propose a binary function similarity comparison method based on Graph Mover's Distance. The model takes two graphs as input, and first learns the spatial structure of the nodes in the graph based on the graph attention neural network to form the node embedding. Then we use the sum of the distance between the two sets of node embeddings to represent the distance between the graphs as the graph similarity index. We conduct experiments on the control flow graph of the program and prove the effectiveness of the method. © 2020 IEEE.

关键词： Embeddings

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A Patch Analysis Method Based on Multi-firmware Comparison 2021

A Patch Analysis Method Based on Multi-firmware Comparison

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2021 International Symposium on Electrical, Electronics and Information engineering, ISEEIE 2021

作者： Xiao, Ruiqing Zhu, Yuefei Hu, Anxiang Zhu, Xiaoya Liu, Shengli State Key Laboratory of Mathematical Engineering and Advanced Computing China

ISBN: (纸本)9781450389839

A major user need is the completion of security audits by locating vulnerability functions using vulnerability information published by firmware manufacturers. However, it is difficult to manually analyze the relatively large number of patch functions involved in firmware updates. A patch analysis method based on multi-firmware comparison is presented in this study. This method narrows the search for suspected patch functions for vulnerability based on the similarities and differences between different firmware series involved in the vulnerability. Suspected patch functions in multiple firmware programs are first located and filtered based on intervals. Finally, a prototype system is implemented. The filtering results for the prototype system are used to manually locate two one-day vulnerabilities. The experimental results demonstrate that the two methods proposed in this study, namely, patch function location in multiple firmware programs and interval-based patch function filtering, effectively narrow the search for suspected patch functions and reduce the difficulty of manual analysis. © 2021 ACM.

关键词： Firmware

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A Survey on Knowledge Graph Representation Learning with Text Information 3

A Survey on Knowledge Graph Representation Learning with Tex...

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3rd World Symposium on Software engineering, WSSE 2021

作者： Wang, Ling Lu, Jicang Zhou, Gang State Key Laboratory of Mathematical Engineering and Advanced Computing China

ISBN: (纸本)9781450384094

Knowledge graph representation learning provides a lot of help for subsequent tasks such as knowledge graph completion, information retrieval, and intelligent question answering. By representing the knowledge graph as low-dimensional dense vectors, these tasks can improve efficiency significantly. However, limited by the sparseness and huge scale of the actual structure, representation learning only from a structural perspective can no longer meet the research needs. To improve the performance, researchers introduced auxiliary information into representation learning. This paper focuses on models using text as auxiliary information, dividing all text-combined models into two categories: Closed-world assumption models and Open-world assumption models. The former is limited by the model's demand for the structural representation of the graph itself, and can only predict the entities and relationships that already exist in the knowledge graph. The latter can handle entities that have not previously been seen during model training, and connect brand-new entities to the knowledge graph, which is more in line with the dynamic trend of the knowledge graph in real world. Open-world assumption models can be further subdivided into multiple types according different joint functions, such as alignment function, fusion function, score function and transformation function. This paper summarizes existing methods in detail and looks forward to future possible research directions. © 2021 ACM.

关键词： Knowledge graph

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Malware detection method based on control flow analysis 7

Malware detection method based on control flow analysis

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7th International Conference on Information Technology: IoT and Smart City, ICIT 2019

作者： Shan, Peng Li, Qingbao Zhang, Ping Gu, Yanyang State Key Laboratory Mathematical Engineering and Advanced Computing China

ISBN: (纸本)9781450376631

With the rapid development of computer technology and the iteration of malware, numerous computer malware detection methods have been proposed, among which malware detection based on machine learning has become an important research direction. Opcode sequences are often used as an important feature of machine learning models for training and testing. However, opcode sequences extracted orderly from raw disassembly text may not adequately reflect the behavior of executables. In order to solve this problem, this paper proposes a new malware detection method based on the control flow of executables. This method analyzes the control flow of executables and extracts execution traces from by the unit of function. This paper uses the execution traces to represent the behavior of the executables and present the execution traces by opcode sequences. In order to improve the training efficiency and reduce the feature dimensionality, this paper propose an x86 intermediate code. Then we convert the opcode sequences into the corresponding intermediate code sequences and vectorize them using Vector Space Model (VSM) for training and testing. This paper implements Naïve Bayes Classifier, Support Vector Machines and Random Forest for classification. The experiment result shows that the Random Forest algorithm has the best performance, with an accuracy of 90.8% and the model establishment time is 22s. Compared with the traditional methods based on disassembly text, the accuracy is improved by 1.4%, compared with the methods using x86 opcode, the efficiency is increased by 62%. © 2019 Association for computing Machinery.

关键词： Malware

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KANsformer for Scalable Beamforming

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IEEE Transactions on Vehicular Technology 2025年

作者： Xie, Xinke Lu, Yang Chi, Chong-Yung Chen, Wei Ai, Bo Niyato, Dusit Beijing Jiaotong University State Key Laboratory of Advanced Rail Autonomous Operation Beijing100044 China Beijing Jiaotong University School of Computer Science and Technology Beijing100044 China National Tsing Hua University Institute of Communications Engineering Department of Electrical Engineering Hsinchu30013 Taiwan Beijing Jiaotong University School of Electronics and Information Engineering Beijing100044 China Nanyang Technological University College of Computing and Data Science 639798 Singapore

This paper proposes an unsupervised deep-learning (DL) approach by integrating Transformer and Kolmogorov-Arnold networks (KAN) termed KANsformer to realize scalable beamforming for mobile communication systems. Specifically, we consider a classic multi-input single-output energy efficiency maximization problem subject to the total power budget. The proposed KANsformer first extracts hidden features via a multi-head self-attention mechanism and then reads out the desired beamforming design via KAN. Numerical results are provided to evaluate the KANsformer in terms of generalization performance, transfer learning and ablation experiment. Overall, the KANsformer outperforms the existing benchmark DL approaches, and is adaptable to the variation in the number of mobile users with real-time and near-optimal inference. © 1967-2012 IEEE.

关键词： Budget control

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Accelerating the cryo-EM structure determination in RELION on GPU cluster

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Frontiers of Computer Science 2022年第3期16卷 21-39页

作者： Xin YOU Hailong YANG Zhongzhi LUAN Depei QIAN Sino-German Joint Software Institute School of Computer Science and EngineeringBeihang UniversityBeijing 100191China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214125

The cryo-electron microscopy(cryo-EM)is one of the most powerful technologies available today for structural *** RELION(Regularized Likelihood Optimization)implements a Bayesian algorithm for cryo-EM structure determination,which is one of the most widely used software in this *** researchers have devoted effort to improve the performance of RELION to satisfy the analysis for the ever-increasing volume of *** this paper,we focus on performance analysis of the most time-consuming computation steps in RELION and identify their performance bottlenecks for specific *** propose several performance optimization strategies to improve the overall performance of RELION,including optimization of expectation step,parallelization of maximization step,accelerating the computation of symmetries,and memory affinity *** experiment results show that our proposed optimizations achieve significant speedups of RELION across representative *** addition,we perform roofline model analysis to understand the effectiveness of our optimizations.

关键词： cryo-EM structure determination performance optimization GPU acceleration RELION

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Embedding Attribute and Relation Information for Person Entity Alignment 6

Embedding Attribute and Relation Information for Person Enti...

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6th International Conference on Big Data and Information Analytics, BigDIA 2020

作者： Wang, Can Liu, Xiaonan Yin, Meijuan State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

Person entity alignment is to distinguish whether the person entity information extracted from different data sources refer to the same entity. Existing methods mainly use attribute and relation information of entity to solve entity alignment problem. Most of them are based on common information of entity, while ignore some non-common but semantically similar attribute information and they only consider the relation between first-order adjacent entity, which makes it difficult to accurately align entity in the case of scarcity of common information. so we propose a person entity alignment method based on joint embedding of attribute and relation information, which makes full use of non-common but related information of entity to align them and improves the Hit@k of alignment results when common information is sparse. In the method, the representation vector of attribute information and the representation vector of relation information are obtained by embedding. During embedding, we consider the identification of different attributes and the second-order relation between entities to improve the role of feature attributes and the second-order relation in entity alignment. When calculating the similarity of entities, binary linear regression model is used to fit the weight of attribute information and relation information similarity, so as to adapt to the different characteristics of the entity data under different circumstances. The experimental results show that, compared with the related methods, the Hit@1 value and Hit@10 value of the proposed method increased by more than 8.4% and more than 9.1% respectively. © 2020 IEEE.

关键词： Embeddings

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SoK: A Survey on Redundant Execution Technology

SoK: A Survey on Redundant Execution Technology

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2021 International Conference on advanced computing and Endogenous Security, ICACES 2021

作者： Liu, Zijing Zhang, Zheng Xi, Ruicheng Zhu, Pengzhe Ma, Bolin State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665424493

Redundant execution technology is one of the effective ways to improve the safety and reliability of computer systems. By rationally configuring redundant resources, adding components with the same function, using the determined redundant execution logic to coordinate and efficiently execute synchronously can effectively ensure high availability of the machine and system. Fault-tolerant is based on redundant execution, which is the primary method of dealing with system hardware failures. Recently, multi-threading redundancy has realized the continuous development of fault-tolerant technology, which makes the processing granularity of the system tolerate random failure factors gradually reduced. At the same time, intrusion tolerant technology has also been continuously developed with the emergence of multi-variant execution technology. It mainly uses the idea of dynamic heterogeneous redundancy to construct a set of variants with equivalent functions and different structures to complete the detection and processing of threats outside the system. We summarize the critical technologies of redundant execution to achieve fault tolerance and intrusion tolerance in recent years, sorts out the role of redundant execution in the development process from fault tolerance technology to intrusion tolerance technology, classify redundant execution technologies at different levels, finally point out the development prospects of redundant execution technology in multiple application fields and future technical research directions. © 2022 IEEE.

关键词： Redundancy

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