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A Note on Determine the Greatest Common Subfamily of Two NFSRs by Grbner Basis

Journal of Systems Science & Complexity 2015年第5期28卷 1231-1242页

作者： WANG Zhongxiao QI Wenfeng TIAN Tian Luoyang University of Foreign Language State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Information Science and Technology Institute

For nonlinear feedback shift registers(NFSRs), their greatest common subfamily may be not unique. Given two NFSRs, the authors only consider the case that their greatest common subfamily exists and is unique. If the greatest common subfamily is exactly the set of all sequences which can be generated by both of them, the authors can determine it by Grbner basis theory. Otherwise, the authors can determine it under some conditions and partly solve the problem.

关键词： Greatest common subfamily Grbner basis nonlinear feedback shift register stream cipher

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The interactive mechanism of static and dynamic analysis in the reverse analysis of embedded software

International Journal of Multimedia and Ubiquitous Engineeri...

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International Journal of Multimedia and Ubiquitous engineering 2016年第10期11卷 33-44页

作者： Tie-Ming, Liu Lie-Hui, Jinag Jing-Si, Zhu Gang, Meng The State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450000 China ZhengZhou University of Science and Technology Zhengzhou450064 China

Because the software reverse analysis method which combined the dynamic and static analyses lacks normative interactive mode, the work of the software reverse analysis is inefficient, and its reusability is poor. Based on dynamic and static analysis process of the embedded software, three kinds of interactive mechanism are proposed, including Static To Dynamic (STD), Dynamic To Static (DTS), Static and Dynamic simultaneous (SDM), and has also presented the method of realizing these three interaction mechanisms in detail. The test results show that interactive mechanisms of STD, DTS and SDM are suitable for correction of abnormal nodes in the results of static analysis, optimization of dynamic information extraction, identification of hidden codes and so on. It can greatly improve work efficiency of the embedded software reverse analysis. © 2016 SERSC.

关键词： Static analysis

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Parallel Image Processing on the Sunway Many-Core Processor

Parallel Image Processing on the Sunway Many-Core Processor

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IEEE International Conference on High Performance computing and Communications (HPCC)

作者： Meiting Zhao Rui Liu Yi Liu Kaida Song Depei Qian State Key Lab of Mathematical Engineering and Advanced Computing Wuxi China Sino-German Joint Software Institute Beihang University Beijing China

ISBN: (纸本)9781509042982

Many image processing algorithms have been parallelized successfully on many-core processors, such as GPU and Intel Xeon Phi. In this paper, we choose the Sunway many-core processor SW26010, which is a new processor designed and made in China that constitutes the current NO.1 supercomputer Sunway TaihuLight. This paper firstly introduces the architecture of Sunway SW26010 processor and two representative image processing algorithms: local binary pattern (LBP) and histogram of oriented gradient (HOG). Furthermore we propose a method of parallel implementation, and the experimental results of this method show that the speedup can be up to 170 for LBP and 33 for HOG. Then two optimized methods are brought forward based on this parallel implementation, including the optimization of program and parallel design. We optimize the program by using the method that combined step transmission and software prefetching. From the experiment results of the first optimization we can know that the maximum speedup can reach 310 for LBP with processing high-resolution images and 83 for HOG. Then we optimize the parallel design by using a coarse grained parallel method, and the experimental results show that the speedup can be up to 370 for LBP and 95 for HOG when processing low-resolution images. Finally, we investigate the scalability of our parallelism on the Sunway TaihuLight with different number of processor nodes, and the experiment results prove that the two algorithms' parallel design and implementation have better expansibility.

关键词： Algorithm design and analysis Image processing Supercomputers Computer architecture Clustering algorithms Optimization Parallel algorithms

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A Rational Secret Sharing Relying on Reputation

A Rational Secret Sharing Relying on Reputation

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International Conference on Intelligent Networking and Collaborative Systems (INCOS)

作者： Jianghao Jin Xie Zhou Chuangui Ma Xu'an Wang State Key laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Henan China Engineering University of CAPF Xi'an Shanxi China

Many of the existing rational protocols do not notice that some behavior of participants may be problematic. These participants themselves do not benefit from the behavior, while it reduces the utilities of other participants. Besides, this behavior will reduce the efficiency of the protocols. In this paper, a novel rational fair exchange protocol is proposed based on the reputation system. The computation of the reputation is completed by the third party, which reduces the computation work of the participants. The rational participants who get higher reputation in our protocol will obtain more utilities. The protocol can deal with the problem above because rational participants always hope to improve their utilities. Compared with other existing protocols, our protocol needs only one round. Furthermore, we prove that our protocol is rational fair.

关键词： Protocols Cryptography Lead Games Nash equilibrium Collaboration

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Improved MOPSO algorithm based on map-reduce model in cloud resource scheduling

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Journal of Computers (Taiwan) 2016年第2期27卷 67-78页

作者： Zhang, Heng-Wei Niu, Kan Wang, Jin-Dong Wang, Na Zhengzhou Institute of Information Science and Technology Zhengzhou450001 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China

A multi-objective resource scheduling model with quality of service (QoS) restriction was built to improve the computing efficiency of Map-Reduce resource scheduling. The model considered the scheduling problem of both Map and Reduce phase and a chaotic multi-objective particle swarm algorithm was proposed to solve the model. The information entropy theory was used to maintain nondomination solution set by the algorithm so as to retain the diversity of solution and the uniformity of distribution. By Sigma methods to achieve fast convergence, chaotic disturbance mechanism was intro-duced to improve the diversity of the population and the ability of global optimization algorithm, which can avoid the algo-rithm from falling into local extremism. The experiments show that the number of iteration in the algorithm obtaining solu-tions is little and nondomination solutions distribute equably. In solving Map-Reduce resource scheduling problems, it indi-cates that the astringency and the diversity of solution set of this algorithm are better than the traditional multi-objective particle swarm algorithm.

关键词： Quality of service

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Thread-aware adaptive prefetcher on multicore systems: Improving the performance for multithreaded workloads

Thread-aware adaptive prefetcher on multicore systems: Impro...

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作者： Liu, Peng Yu, Jiyang Huang, Michael C. College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi214125 China Department of Shannon Lab. Huawei Technologies Co. Ltd. Hangzhou310051 China Department of Electrical and Computer Engineering University of Rochester RochesterNY14627-0231 United States

Most processors employ hardware data prefetching techniques to hide memory access latencies. However, the prefetching requests from different threads on a multicore processor can cause severe interference with prefetching and/or demand requests of others. The data prefetching can lead to significant performance degradation due to shared resource contention on shared memory multicore systems. This article proposes a thread-aware data prefetching mechanism based on low-overhead runtime information to tune prefetching modes and aggressiveness, mitigating the resource contention in the memory system. Our solution has three new components: (1) a self-tuning prefetcher that uses runtime feedback to dynamically adjust data prefetching modes and arguments of each thread, (2) a filtering mechanism that informs the hardware about which prefetching request can cause shared data invalidation and should be discarded, and (3) a limiter thread acceleration mechanism to estimate and accelerate the critical thread which has the longest completion time in the parallel region of execution. On a set of multithreaded parallel benchmarks, our thread-aware data prefetchingmechanism improves the overall performance of 64-core system by 13% over a multimode prefetch baseline system with two-level cache organization and conventional modified, exclusive, shared, and invalid-based directory coherence *** compare our approach with the feedback directed prefetching technique and find that it provides 9% performance improvement on multicore systems, while saving the memory bandwidth consumption.

关键词： Benchmarking

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Restricted Boltzmann Machines and Deep Belief Networks on Sunway Cluster

Restricted Boltzmann Machines and Deep Belief Networks on Su...

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IEEE International Conference on High Performance computing and Communications

作者： Kaida Song Yi Liu Rui Wang Meiting Zhao Ziyu Hao Depei Qian Sino-German Joint Software Institute Beihang University. Beijing China State Key Lab of Mathematical Engineering and Advanced Computing Wuxi China

ISBN: (纸本)9781509042982

Deep learning models have showed great potential in classification and recognition over the last decade. Deep Belief Networks (DBNs) have been applied in visual, voice fields due to their great feature presentation capability. However, there are a vast number of time consuming calculations in the training of DBNs. Many researches have accelerated the training of DBNs with good speedups on CPU, GPU, FPGA, etc. At the same time, the latest published Sunway(SW) many-core processor has high computing performance and dedicated heterogeneous architecture. This paper provides a DBNs training system on SW cluster and verifies SW cluster's applicability of training DBNs. We firstly optimize the Restricted Boltzmann Machines and Deep Belief Networks on Sunway processor, then build a parallelism model with linear topology to train DBNs on multiple processors. The system is implemented on the TaihuLight supercomputer and evaluated by training a DBN with 2.8 million parameters with MNIST dataset. Experimental results show that our system achieves considerable speedups on Sunway processors as compared with CPUs.

关键词： Sunway processor TaihuLight supercomputer Restricted Boltzmann Machines Deep Belief Networks data parallelism model

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Population of Merging Compact Binaries Inferred Using Gravitational Waves through GWTC-3

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Physical Review X 2023年第1期13卷 011048-011048页

作者： R. Abbott T. D. Abbott F. Acernese K. Ackley C. Adams N. Adhikari R. X. Adhikari V. B. Adya C. Affeldt D. Agarwal M. Agathos K. Agatsuma N. Aggarwal O. D. Aguiar L. Aiello A. Ain P. Ajith T. Akutsu P. F. de Alarcón S. Akcay S. Albanesi A. Allocca P. A. Altin A. Amato C. Anand S. Anand A. Ananyeva S. B. Anderson W. G. Anderson M. Ando T. Andrade N. Andres T. Andrić S. V. Angelova S. Ansoldi J. M. Antelis S. Antier F. Antonini S. Appert Koji Arai Koya Arai Y. Arai S. Araki A. Araya M. C. Araya J. S. Areeda M. Arène N. Aritomi N. Arnaud M. Arogeti S. M. Aronson K. G. Arun H. Asada Y. Asali G. Ashton Y. Aso M. Assiduo S. M. Aston P. Astone F. Aubin C. Austin S. Babak F. Badaracco M. K. M. Bader C. Badger S. Bae Y. Bae A. M. Baer S. Bagnasco Y. Bai L. Baiotti J. Baird R. Bajpai M. Ball G. Ballardin S. W. Ballmer A. Balsamo G. Baltus S. Banagiri D. Bankar J. C. Barayoga C. Barbieri B. C. Barish D. Barker P. Barneo F. Barone B. Barr L. Barsotti M. Barsuglia D. Barta J. Bartlett M. A. Barton I. Bartos R. Bassiri A. Basti M. Bawaj J. C. Bayley A. C. Baylor M. Bazzan B. Bécsy V. M. Bedakihale M. Bejger I. Belahcene V. Benedetto D. Beniwal T. F. Bennett J. D. Bentley M. BenYaala F. Bergamin B. K. Berger S. Bernuzzi C. P. L. Berry D. Bersanetti A. Bertolini J. Betzwieser D. Beveridge R. Bhandare U. Bhardwaj D. Bhattacharjee S. Bhaumik I. A. Bilenko G. Billingsley S. Bini R. Birney O. Birnholtz S. Biscans M. Bischi S. Biscoveanu A. Bisht B. Biswas M. Bitossi M.-A. Bizouard J. K. Blackburn C. D. Blair D. G. Blair R. M. Blair F. Bobba N. Bode M. Boer G. Bogaert M. Boldrini L. D. Bonavena F. Bondu E. Bonilla R. Bonnand P. Booker B. A. Boom R. Bork V. Boschi N. Bose S. Bose V. Bossilkov V. Boudart Y. Bouffanais A. Bozzi C. Bradaschia P. R. Brady A. Bramley A. Branch M. Branchesi J. Brandt J. E. Brau M. Breschi T. Briant J. H. Briggs A. Brillet M. Brinkmann P. Brockill A. F. Brooks J. Brooks D. D. Brown S. Brunett G. Bruno R. Bruntz J. Bryant T. Bulik H. J. Bulten A. Buonanno R. Buscicchio D. Buskulic C. Buy R. L. Byer L. Cadonati LIGO Laboratory California Institute of Technology Pasadena California 91125 USA Louisiana State University Baton Rouge Louisiana 70803 USA Dipartimento di Farmacia Università di Salerno I-84084 Fisciano Salerno Italy INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo I-80126 Napoli Italy OzGrav School of Physics & Astronomy Monash University Clayton 3800 Victoria Australia LIGO Livingston Observatory Livingston Louisiana 70754 USA University of Wisconsin-Milwaukee Milwaukee Wisconsin 53201 USA OzGrav Australian National University Canberra Australian Capital Territory 0200 Australia Max Planck Institute for Gravitational Physics (Albert Einstein Institute) D-30167 Hannover Germany Leibniz Universität Hannover D-30167 Hannover Germany Inter-University Centre for Astronomy and Astrophysics Pune 411007 India University of Cambridge Cambridge CB2 1TN United Kingdom Theoretisch-Physikalisches Institut Friedrich-Schiller-Universität Jena D-07743 Jena Germany University of Birmingham Birmingham B15 2TT United Kingdom Center for Interdisciplinary Exploration & Research in Astrophysics (CIERA) Northwestern University Evanston Illinois 60208 USA Instituto Nacional de Pesquisas Espaciais 12227-010 São José dos Campos São Paulo Brazil Gravity Exploration Institute Cardiff University Cardiff CF24 3AA United Kingdom INFN Sezione di Pisa I-56127 Pisa Italy International Centre for Theoretical Sciences Tata Institute of Fundamental Research Bengaluru 560089 India Gravitational Wave Science Project National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan Universitat de les Illes Balears IAC3–IEEC E-07122 Palma de Mallorca Spain University College Dublin Dublin 4 Ireland INFN Sezione di Torino I-10125 Torino Italy Università di Napoli “Federico II” Complesso Universitario di Monte S. Angelo I-80126 Napoli

We report on the population properties of compact binary mergers inferred from gravitational-wave observations of these systems during the first three LIGO-Virgo observing runs. The Gravitational-Wave Transient Catalog 3 (GWTC-3) contains signals consistent with three classes of binary mergers: binary black hole, binary neutron star, and neutron star–black hole mergers. We infer the binary neutron star merger rate to be between 10 and 1700 Gpc−3 yr−1 and the neutron star–black hole merger rate to be between 7.8 and 140 Gpc−3 yr−1, assuming a constant rate density in the comoving frame and taking the union of 90% credible intervals for methods used in this work. We infer the binary black hole merger rate, allowing for evolution with redshift, to be between 17.9 and 44 Gpc−3 yr−1 at a fiducial redshift (z=0.2). The rate of binary black hole mergers is observed to increase with redshift at a rate proportional to (1+z)κ with κ=2.9−1.8+1.7 for z≲1. Using both binary neutron star and neutron star–black hole binaries, we obtain a broad, relatively flat neutron star mass distribution extending from 1.2−0.2+0.1 to 2.0−0.3+0.3M⊙. We confidently determine that the merger rate as a function of mass sharply declines after the expected maximum neutron star mass, but cannot yet confirm or rule out the existence of a lower mass gap between neutron stars and black holes. We also find the binary black hole mass distribution has localized over- and underdensities relative to a power-law distribution, with peaks emerging at chirp masses of 8.3−0.5+0.3 and 27.9−1.8+1.9M⊙. While we continue to find that the mass distribution of a binary’s more massive component strongly decreases as a function of primary mass, we observe no evidence of a strongly suppressed merger rate above approximately 60M⊙, which would indicate the presence of a upper mass gap. Observed black hole spins are small, with half of spin magnitudes below χi≈0.25. While the majority of spins are preferentially aligned wi

关键词： Gravitational wave sources Gravitational waves Gravitational wave detection

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Information diffusion network inferring and pathway tracking

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Science China(Information Sciences) 2015年第9期58卷 135-149页

作者： ZHOU DongHao HAN WenBao WANG YongJun YUAN BaoDi College of Computer National University of Defense Technology State Key Laboratory of Mathematical Engineering and Advanced Computing College of Computer Science and Technology Fudan University

Network diffusion, such as spread of ideas, rumors, contagious disease, or a new type of behaviors, is one of the fundamental processes within networks. Designing effective strategies for influence spread maximization, rumor spread minimization, or epidemic immunization has attracted considerable research attention. However, a key challenge is that many times we can only observe the trace of contagion spreading across network, but the underlying network structure is unknown and the transmission rates between node pairs are unclear to us. In this paper, given the observed information cascades, we aim to address two problems:diffusion network structure inferring and information diffusion pathways tracking. We propose a novel probabilistic model called Network Inferring from Multidimensional Features of Cascades(NIMFC) which takes into account heterogeneous features, including temporal and topological features of cascades, node attributes, and information content, to infer the latent network structure and transmission rates of edges. Also, based on the inferred network structure, we may track diffusion pathways of a cascade in social networks. We use blocked coordinate descent method to learn a sparse estimation of the latent network. Our proposed model NIMFC is evaluated both on large synthetic and real-world data sets, and experimental results show that our method significantly outperforms state-of-the-art models both in terms of recovering the latent network structure and information pathway tracking.

关键词： diffusion network network inferring information pathway tracking temporal feature node attributes topological feature informatio

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VMKDO: Verifiable multi-keyword search over encrypted cloud data for dynamic data-owner

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Peer-to-Peer Networking and Applications 2016年第2期11卷 287-297页

作者： Yinbin Miao Jianfeng Ma Ximeng Liu Zhiquan Liu Limin Shen Fushan Wei State Key Laboratory of Integrated Services Networks Xidian University Xi’an China School of Information Systems Singapore Management University Singapore Singapore State Key Laboratory of Mathematical Engineering and Advanced Computing The PLA Information Engineering University Zhengzhou China

The advantages of cloud computing encourage individuals and enterprises to outsource their local data storage and computation to cloud server, however, data security and privacy concerns seriously hinder the practicability of cloud storage. Although searchable encryption (SE) technique enables cloud server to provide fundamental encrypted data retrieval services for data-owners, equipping with a result verification mechanism is still of prime importance in practice as semi-trusted cloud server may return incorrect search results. Besides, single keyword search inevitably incurs many irrelevant results which result in waste of bandwidth and computation resources. In this paper, we are among the first to tackle the problems of data-owner updating and result verification simultaneously. To this end, we devise an efficient cryptographic primitive called as verifiable multi-keyword search over encrypted cloud data for dynamic data-owner scheme to protect both data confidentiality and integrity. Rigorous security analysis proves that our scheme is secure against keyword guessing attack (KGA) in standard model. As a further contribution, the empirical experiments over real-world dataset show that our scheme is efficient and feasible in practical applications.

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