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Reducing DRAM refreshing in an error correction manner

Science China Chemistry 2015年第12期58卷 186-199页

作者： ZHU DanFeng WANG Rui WEI YanJiang QIAN DePei School of Computer Science and Engineering Beihang University State Key Laboratory of Mathematical Engineering and Advanced Computing

Dynamic random access memory(DRAM) is facing the challenge of technology scaling. The decreasing feature size makes it harder to make DRAM cells which can keep the current data-holding time. When DRAM cells cannot hold data for a long time, DRAM chips need a more frequent refreshing operation. Therefore, in the near future, time and energy cost on DRAM refreshing will be no longer trivial. In this paper, we propose DRAM Error Correction Pointer(ECP), an error-correction-manner framework, to reduce DRAM refreshes without data loss. We exploit the non-uniform feature of DRAM cells with respect to the data retention time. Compared with the conventional refreshing mechanisms, which refresh DRAM chips by the retention time of the leakiest cells, we refresh the chips much fewer times, and treat the not-in-time refreshed cells as fault elements. We use the structure of ECP as a fault tolerant element. By recording the data which are supposed to be written into the leaky cells in our DRAM-ECP structures, DRAM-ECP can significantly decrease refreshing frequency. When these data are to be read out, DRAM-ECP retrieves the data stored in ECPs and covers them to the corresponding position in the data row. Our experiments show that DRAM-ECP can reduce over 70%refreshing operations than the current refreshing mechanism and also get significant energy saving.

关键词： DRAM refreshing error correction DRAM-ECP counting bloom filter retention time

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On the complete weight distributions of quantum error-correcting codes

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Chinese Physics B 2023年第5期32卷 272-287页

作者：杜超马智熊茂胜 State Key Laboratory of Mathematical Engineering and Advanced Computing Zhenghzhou 450001China Henan Key Laboratory of Network Cryptography Technology Zhenghzhou 450001China Department of Mathematics Hong Kong University of Science and TechnologyHong KongChina

In a recent paper, Hu et al. defined the complete weight distributions of quantum codes and proved the Mac Williams identities, and as applications they showed how such weight distributions may be used to obtain the singleton-type and hamming-type bounds for asymmetric quantum codes. In this paper we extend their study much further and obtain several new results concerning the complete weight distributions of quantum codes and applications. In particular, we provide a new proof of the Mac Williams identities of the complete weight distributions of quantum codes. We obtain new information about the weight distributions of quantum MDS codes and the double weight distribution of asymmetric quantum MDS codes. We get new identities involving the complete weight distributions of two different quantum codes. We estimate the complete weight distributions of quantum codes under special conditions and show that quantum BCH codes by the Hermitian construction from primitive, narrow-sense BCH codes satisfy these conditions and hence these estimate applies.

关键词： quantum codes complete weight distributions Mac Williams identities BCH codes

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VFDETECT: A Vulnerable Code Clone Detection System Based on Vulnerability Fingerprint 3

VFDETECT: A Vulnerable Code Clone Detection System Based on ...

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2017 IEEE 第3届信息技术与机电一体化工程国际学术会议(ITOEC 2017)

作者： Zhen Liu Qiang Wei Yan Cao State Key Laboratory of Mathematical Engineering and Advanced Computing China National Digital Switching System Engineering and Technological Research Center

Vulnerable code reuse in open source software is a serious threat to software ***,the existing highefficiency methods for vulnerable code clone detection have a large number of false-nega

ISBN: (纸本)9781509053643;9781509053636

Vulnerable code reuse in open source software is a serious threat to software ***,the existing highefficiency methods for vulnerable code clone detection have a large number of false-nega

关键词： Cloning Fingerprint recognition Feature extraction Linux Kernel Data structures

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Optimizing execution for pipelined-based distributed deep learning in a heterogeneously networked GPU cluster

Optimizing execution for pipelined-based distributed deep le...

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作者： Zhang, Jinghui Zhan, Jun Li, Jiange Jin, Jiahui Qian, Lei School of Computer Science and Engineering Southeast University Nanjing China State Key Lab of Mathematical Engineering and Advanced Computing Wuxi China

Exorbitant resources (computing and memory) are required to train a deep neural network (DNN). Often researchers deploy an approach that uses distributed parallel training to acquire larger models faster on GPUs. This approach has its detriments, though;on one hand, a GPU's expanded capacity to compute also produces bigger bottlenecks in inter-GPU's communications during model training, and multi-GPU systems lead to complex connectivity. Workload schedulers then end up having to consider hardware topology and requirements for workload communication, in hopes of allocating GPU resources to optimize execution time and improve usage in a heterogeneous environment. On the other hand, the high memory requirements to train a DNN model make running the training processes on GPUs onerous. To contend with this, we introduce two execution optimization methods based on pipeline-hybrid parallelism (using both data and model parallelism) in a GPU cluster with heterogeneous networking. First, we propose a model partition algorithm that accelerates pipeline-hybrid parallelism training between heterogeneously network-connected GPUs. Second, we introduce a cost-balanced recomputing algorithm to reduce memory usage in the pipeline mode. Experiments show that our solution (Pipe-Torch) averages a speedup of 1.4× compared with data parallelism, and reduces the memory footprint while maintaining pipelined load-balanced training. © 2020 John Wiley & Sons Ltd

关键词： Pipelines

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Empirical investigation of stochastic local search for maximum satisfiability

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Frontiers of Computer Science 2019年第1期13卷 86-98页

作者： Yi CHU Chuan LUO Shaowei CAI Haihang YOU State Key Laboratory of Computer Architecture Institute of Computing TechnologyChinese Academy of Sciences Beijing 100190China University of Chinese Academy of Sciences Beijing 100049China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214125China State Key Laboratory of Computer Science Institute of SoftwareChinese Academy of SciencesBeijing 100190China

The maximum satisfiability (MAX-SAT)problem is an important NP-hard problem in theory,and has a broad range of applications in *** local search (SLS)is becoming an increasingly popular method for solving ***,a powerful SLS algorithm called CCLS shows efficiency on solving random and crafted MAX-SAT ***,the performance of CCLS on solving industrial MAX-SAT instances lags far *** this paper,we focus on experimentally analyzing the performance of SLS algorithms for solving industrial MAXSAT ***,we conduct experiments to analyze why CCLS performs poor on industrial *** we propose a new strategy called additive BMS (Best from Multiple Selections)to ease the serious *** integrating CCLS and additive BMS,we develop a new SLS algorithm for MAXSAT called CCABMS,and related experiments indicate the efficiency of ***,we experimentally analyze the effectiveness of initialization methods on SLS algorithms for MAX-SAT,and combine an effective initialization method with CCABMS,resulting in an enhanced *** results show that our enhanced algorithm performs better than its state-of-the-art SLS competitors on a large number of industrial MAX-SAT instances.

关键词： empirical investigation stochastic local search maximum satisfiability industrial instances additive BMS

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Rotation Model Enhancement for Adversarial Attack

Rotation Model Enhancement for Adversarial Attack

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2022 International Conference on Networking and Network Applications, NaNA 2022

作者： Zhang, Hengwei Li, Zheming Liu, Hao Yang, Bo Li, Chenwei Wang, Jindong State Key Laboratory of Mathematical Engineering and Advanced Computing Henan Key Laboratory of Information Security Zhengzhou China

ISBN: (数字)9781665461313

ISBN: (纸本)9781665461313

Current white-box attack to deep neural networks have achieved considerable success, but not for black-box attack. The main reason is poor transferability, as the adversarial examples are crafted with single deep neural networks model, and excessively depend on that model. To address that problem, we propose a rotation model enhancement algorithm to craft adversarial examples. We improve rotation method in model enhancement. This algorithm constructs a possibility model to randomly rotate original images, and generates multiple transformed images. Therefore, we craft adversarial examples with single model, and boost attack on multiple models, which demonstrate considerable transferability and success rate for black-box attack. The simulation indicates the algorithm boost black-box attack with a 89.2% success rate. © 2022 IEEE.

关键词： Deep neural networks

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Misleading Image Classification with Multi-shearing and Random Padding 6

Misleading Image Classification with Multi-shearing and Rand...

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6th International Conference on Electronic Information Technology and Computer engineering, EITCE 2022

作者： Li, Chenwei Li, Zheming Yang, Bo Zhang, Hengwei State Key Laboratory of Mathematical Engineering and Advanced Computing Henan Key Laboratory of Information Security Zhengzhou China

ISBN: (纸本)9781450397148

Neural networks are vulnerable when input data is applied with human-imperceptible perturbations, which is called adversarial examples. When used in image classification models, adversarial examples mislead neural netwoks to classify images with wrong labels, posing great threat to network security. White-box attack has achieved considerable success rate, for the model structure is already known. But black-box attack remains to be improved, so as to the transferability. We refer to the model augmentation method in network training process, and apply to generating adversarial examples to reduce overfitting. Consulting fundamental methods in adversarial examples, we propose a multi-cropping transformation method to alleviate overfitting and enhance transferability. Firstly, referring to data augmentation, we multi-crop original images in every iteration with random possibilities in adversarial exaples generating process. Secondly, the gradient of model loss function is calculated, and the perturbations are added to original images. Finally, we generate adversarial examples with iterative perturbations. The validation of our method is verified on single models and ensemble models, and the transferability is improved, compared to other fundamental methods. © 2022 Association for computing Machinery.

关键词： Shearing

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Anti-JPEG Compression Steganography Based on the High Tense Region Locating Method

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Computers, Materials & Continua 2019年第4期59卷 199-214页

作者： Yang Wu Weiping Shang Jiahao Chen State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450002China School of Telecommunications Engineering Xidian UniversityXi’an710071China Zhuhai Campus of Beijing Normal University Zhuhai519000China

Robust data hiding techniques attempt to construct covert communication in a lossy public ***,the existing robust JPEG steganographic algorithms cannot overcome the side-information missing ***,this paper proposes a new robust JPEG steganographic algorithm based on the high tense region location method which needs no side-information of lossy ***,a tense region locating method is proposed based on the Harris-Laplacian feature ***,robust cover object generating processes are ***,the advanced embedding cost function is proposed.A series of experiments are conducted on various JPEG image sets and the results show that the proposed steganographic algorithm can resist JPEG compression efficiently with acceptable performance against steganalysis statistical detection libraries GFR(Gabor Filters Rich model)and DCTR(Discrete Cosine Transform Residual).

关键词： Robust data hiding steganography JPEG compression resistant Harris-Laplacian feature

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Traceability Method of Network Attack Based on Evolutionary Game

Traceability Method of Network Attack Based on Evolutionary ...

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2022 International Conference on Networking and Network Applications, NaNA 2022

作者： Zhang, Hengwei Zhang, Xiaoning Sun, Pengyu Liu, Xiaohu Ma, Junqiang Zhang, Yuchen State Key Laboratory of Mathematical Engineering and Advanced Computing Henan Key Laboratory of Information Security Zhengzhou China

ISBN: (数字)9781665461313

ISBN: (纸本)9781665461313

Cyberspace is vulnerable to continuous malicious attacks. Traceability of network attacks is an effective defense means to curb and counter network attacks. In this paper, the evolutionary game model is used to analyze the network attack and defense behavior. On the basis of the quantification of attack and defense benefits, the replication dynamic learning mechanism is used to describe the change process of the selection probability of attack and defense strategies, and finally the evolutionary stability strategies and their solution curves of both sides are obtained. On this basis, the attack behavior is analyzed, and the probability curve of attack strategy and the optimal attack strategy are obtained, so as to realize the effective traceability of attack behavior. © 2022 IEEE.

关键词： Network security

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A NEW SCHEME BASED ON THE MI SCHEME AND ITS ANALYSIS

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Journal of Electronics(China) 2013年第2期30卷 198-203页

作者： Jiao Luyao Li Yifa Qiao Shuaiting Department of Information Science Zhengzhou Information Science and Technology Institute State Key Laboratory of Mathematical Engineering and Advanced Computing

This article aims at designing a new Multivariate Quadratic (MQ) public-key scheme to avoid the linearization attack and differential attack against the Matsumoto-Imai (MI) scheme. Based on the original scheme, our new scheme, named the Multi-layer MI (MMI) scheme, has a structure of multi-layer central map. Firstly, this article introduces the MI scheme and describes linearization attack and differential attack; then prescribes the designation of MMI in detail, and proves that MMI can resist both linearization attack and differential attack. Besides, this article also proves that MMI can resist recent eXtended Linearization (XL)-like methods. In the end, this article concludes that MMI also maintains the efficiency of MI.

关键词： Multivariate Quadratic (MQ) Public-key Cryptosystem (PKC) Matsumoto-Imai (MI) Central map Linearization attack Differential attack eXtended Linearization (XL)

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