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Register one-to-one mapping strategy in dynamic binary translation

International Conference on Network Security and Communication engineering, NSCE 2014

作者： Cui, Y.N. Pang, J.M. Shan, Z. Yue, F. State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781138028210

Dynamic Binary Translation (DBT) is an important technology to cross-platform software transplantation such as enhancing the compatibility of Alpha. However, there exist some factors that impede its performance: high translation overhead and translated code of low quality. In this work, we take advantage of host registers, using register mapping strategy to promote the performance of DBT. By mapping registers from guest Instruction-Set Architectures (ISA) to host machines, it could off-load the overhead caused by load and store operations of memory. By simplifying the rules of the intermediate code generated, it could lower the number of intermediate code and improve the quality of translated code. Form X86 to ALPHA on SPEC 2006, the code expansion reduces 32.86% and the performance of the optimized translator is improved by 7.55%. © 2015 Taylor & Francis Group, London.

关键词： Mapping

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A key point method for data registration for multi-sensor fusion 16

A key point method for data registration for multi-sensor fu...

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16th International Conference of the European Society for Precision engineering and Nanotechnology, EUSPEN 2016

作者： Zeng, Wenhan Jiang, Xiangqian Lou, Shan Scott, Paul EPSRC Centre for Innovative Manufacturing in Advanced Metrology School of Computing and Engineering University of Huddersfield HD33DH United Kingdom State Key Lab of Digital Manufacture and Equipment School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan Hubei430074 China

ISBN: (纸本)9780956679086

It has been recognized that multi-sensor data fusion can provide a more holistic, accurate and reliable information of the measured surface. Data registration, which is used to align data into one coordinate system, is a key step of data fusion. Widely used feature-based methods find correspondence between features, and then a geometrical transformation is determined to map the target data to the reference data. Reliable and accurate feature selection is thus very important for data registration. In this research, a reliable key point method called Scale Invariant Feature Method (SIFM) for data registration is investigated. By using this method, for each data, one can build a set of feature descriptors of the defined key points, which have the scale/shift/rotation invariant properties. Then the correspondence of two data and geometrical transformation can be achieved by finding the matching of two feature descriptors through closeness measurement. Initial tests on freeform and structured surfaces have proven the effectiveness and efficiency of the method.

关键词： Sensor data fusion

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PACM: A Prediction-Based Auto-Adaptive Compression Model for HDFS

PACM: A Prediction-Based Auto-Adaptive Compression Model for...

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IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Ruijian Wang Chao Wang Li Zha University of the Chinese Academy of Sciences Beijing China Institute of Computing Technology Chinese Academy of Sciences Beijing China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi China

ISBN: (纸本)9781509036837

Nowadays the digital universe becomes larger and larger. The data created every year has been up to ZB level. How to store the data in many normal servers is a critical issue. Although a distributed file system alleviates the storage problem, there is still a need to reduce the storage and speed up transmission of largescale data. The distributed file system like HDFS already offers compression schemes to cater to the need, however, when the workload and data format change, configuring the compression with only one kind of algorithm is not always effective. In this paper, we proposed a model called PACM (Prediction-based Auto-adaptive Compression Model) to optimize the storage and performance by using different algorithms, e.g. quicklz, zlib, snappy according to variable data format and workload. We also implemented the model inHadoop and our empirical evaluation shows that by using PACM, the write throughput has been improved by 2-5 times.

关键词： Adaptation models Compression algorithms Data models Prediction algorithms Load modeling Predictive models Throughput

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GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo during the Second Part of the Third Observing Run

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Physical Review X 2023年第4期13卷 041039-041039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 S. Akcay T. Akutsu 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 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 G. S. Cabourn Davies L. Cadonati G. Cagn 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 and 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 University College Dublin Dublin 4 Ireland 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 INFN Sezione di Torino I-10125 Torino Italy Università di Napoli “Federico II” Complesso Universitario di Monte S. Angelo I-80126 Napoli Italy Université de Lyon Université Claude Bernard Lyon 1 CNRS Institut L

The third Gravitational-Wave Transient Catalog (GWTC-3) describes signals detected with advanced LIGO and advanced Virgo up to the end of their third observing run. Updating the previous GWTC-2.1, we present candidate gravitational waves from compact binary coalescences during the second half of the third observing run (O3b) between 1 November 2019, 15∶00 Coordinated Universal Time (UTC) and 27 March 2020, 17∶00 UTC. There are 35 compact binary coalescence candidates identified by at least one of our search algorithms with a probability of astrophysical origin pastro>0.5. Of these, 18 were previously reported as low-latency public alerts, and 17 are reported here for the first time. Based upon estimates for the component masses, our O3b candidates with pastro>0.5 are consistent with gravitational-wave signals from binary black holes or neutron-star–black-hole binaries, and we identify none from binary neutron stars. However, from the gravitational-wave data alone, we are not able to measure matter effects that distinguish whether the binary components are neutron stars or black holes. The range of inferred component masses is similar to that found with previous catalogs, but the O3b candidates include the first confident observations of neutron-star–black-hole binaries. Including the 35 candidates from O3b in addition to those from GWTC-2.1, GWTC-3 contains 90 candidates found by our analysis with pastro>0.5 across the first three observing runs. These observations of compact binary coalescences present an unprecedented view of the properties of black holes and neutron stars.

关键词： Gravitational waves

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Smart Robots: Self‐Propelled 3D‐Printed “Aircraft Carrier” of Light‐Powered Smart Micromachines for Large‐Volume Nitroaromatic Explosives Removal (Adv. Funct. Mater. 39/2019)

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advanced Functional Materials 2019年第39期29卷

作者： Lei Kong Adriano Ambrosi Muhammad Zafir Mohamad Nasir Jianguo Guan Martin Pumera Division of Chemistry and Biological Chemistry School of Physical and Mathematical Sciences Nanyang Technological University Singapore 637371 Singapore State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of Technology 122 Luoshi road Wuhan 430070 P. R. China Department of Inorganic Chemistry University of Chemistry and Technology Prague Technická 5 166 28 Prague 6 Czech Republic Future Energy and Innovation Lab Central European Institute of Technology Brno University of Technology Purkyňova 656/123 Brno CZ‐616 00 Czech Republic Department of Chemical and Biomolecular Engineering Yonsei University 50 Yonsei‐ro Seodaemun‐gu Seoul 03722 Korea

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Virtual channel based aggregated multi-source multicast across backbone

Virtual channel based aggregated multi-source multicast acro...

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International Conference on Control engineering and Information System, ICCEIS 2014

作者： Chen, Y. Li, C.L. Huang, K.X. Zhang, X.B. State Key Laboratory of Mathematical Engineering and Advanced Computing ZhengzhouHenan China

ISBN: (纸本)9781138026858

To achieve the tradeoff between state aggregation and traffic redundancy, different branches of the tree are formed in backbone and receivers’ access networks. In receivers’ access network, each branch corresponds to a multicast group;while in the backbone and on the paths of senders to backbone, each branch corresponds to a multicast traffic class, which achieves multicast states aggregation. Simulation results show that VC-AMSM will result in some traffic redundancy, but it can greatly reduce the number of multicast states and control messages in the network. And the one-tree-one-traffic-class characteristic provides a preferable basis to reconfigure the routing to label switching. © 2015 Taylor & Francis Group, London.

关键词： Redundancy

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Automatic binary de-obfuscation based compiler optimization 6th

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6th International Conference on Swarm Intelligence, ICSI 2015 held in conjunction with the 2nd BRICS Congress on Computational Intelligence, CCI 2015

作者： Lin, Wei Fei, Jin-Long Cai, Rui-Jie State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450002 China

ISBN: (纸本)9783319204710

Junk code increase manual analysis difficulty in reverse engineering, and seriously disturb the automatic analysis process of ant code obfuscating, so find a junk code removing method has a great significance in the field of reverse engineering. Based on this, aiming at the problem that the executable context-dependent junk code is difficult to remove automatically, this paper proposes a junk code removing method based on idle register slicing, through analyzing data dependencies between instructions, get all the idle register of all instruction in code block, slice the code block by idle registers respectively, remove all the junk code in the slice instruction. Experiments show that, this method can remove embedded executable junk code rapidly and accurately, improve the efficiency of reverse engineering. © Springer International Publishing Switzerland 2015.

关键词： Reverse engineering

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keyword search over encrypted data in cloud computing from lattices in the standard model 2nd

Keyword search over encrypted data in cloud computing from l...

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2nd International Conference on Cloud computing and Big Data, CloudCom-Asia 2015

作者： Gu, Chunxiang Zheng, Yonghui Kang, Fei Xin, Dan State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China

ISBN: (纸本)9783319284293

As cloud computing becomes popular, more and more sensitive information are being centralized into the cloud. Hence, we need some mechanism to support operations on encrypted data in many applications in cloud. Public key encryption with keyword search (PEKS) is a mechanism for searching on encrypted data. It enables user Alice to send a secret value TW to a cloud server that will enable the server to selectively retrieve encrypted messages containing the keyword, but learn nothing else. In this paper, we propose a PEKS scheme using lattices. Lattice-based cryptosystems are becoming an increasingly popular in the research community. Our scheme can be proven secure in the standard model with the hardness of the standard Learning With Errors problem. © Springer International Publishing Switzerland 2015.

关键词： Cloud computing

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Scalable QoS multicast provisioning in wide-sense circuit tree

Scalable QoS multicast provisioning in wide-sense circuit tr...

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International Conference on Control engineering and Information System, ICCEIS 2014

作者： Huang, K.X. Chen, Y. Li, C.L. Zhang, X.B. State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Henan China

ISBN: (纸本)9781138026858

It is still a hot topic that how to provide dynamic reconfigurable QoS multicast service in the network. The MPLS network combined with the DiffServ can provide end-to-end QoS guarantee for differentiated services, and aggregated multicast can reduce the cost of maintaining multicast state. In this paper, based on the technology of the Wide-sense circuit Tree technique, we propose an architecture to provide the dynamic QoS multicast service, in the reconfigurable network environment. With the idea of aggregated multicast to reduce multicast state, and using the Wide-sense circuit technology to guarantee the quality of the transport service. © 2015 Taylor & Francis Group, London.

关键词： Quality of service

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Performance Analysis of GPU-Based Convolutional Neural Networks

Performance Analysis of GPU-Based Convolutional Neural Netwo...

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International Conference on Parallel Processing (ICPP)

作者： Xiaqing Li Guangyan Zhang H. Howie Huang Zhufan Wang Weimin Zheng Tsinghua National Laboratory for Information Science and Technology State Key Lab of Mathematical Engineering and Advanced Computing Wuxi China Department of Computer Science and Technology Tsinghua University Department of Electrical and Computer Engineering George Washington University

ISBN: (纸本)9781509028245

As one of the most important deep learning models, convolutional neural networks (CNNs) have achieved great successes in a number of applications such as image classification, speech recognition and nature language understanding. Training CNNs on large data sets is computationally expensive, leading to a flurry of research and development of open-source parallel implementations on GPUs. However, few studies have been performed to evaluate the performance characteristics of those implementations. In this paper, we conduct a comprehensive comparison of these implementations over a wide range of parameter configurations, investigate potential performance bottlenecks and point out a number of opportunities for further optimization.

关键词： Convolution Graphics processing units Runtime Training Computational modeling Computer architecture Kernel

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