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33rd International Conference on Massive Storage Systems and technology, MSST 2017

作者： Li, Shenglong Zhang, Quanlu Yang, Zhi Dai, Yafei Peking University China Institute of Big Data Technologies Shenzhen Key Lab for Cloud Computing Technology and Applications China

In-memory key-value store KV-store is a crucial building block for many systems including large-scale web services and databases. Recent research works pay close attention to data availability of in-memory KV-store. Replication is a common solution to achieve data availability, but the significant memory consumption makes it not applicable for memoryintensive applications. Integrating erasure coding into inmemory KV-store is an emerging approach to achieve memory efficiency. However, traditional in-place update mechanism of erasure coding incurs significant bandwidth cost for writeintensive workload due to frequent broadcast of data update. In this paper, we build BCStore, a bandwidth-efficient inmemory KV-store with erasure coding. We propose a novel batch coding mechanism to optimize the bandwidth cost, and verify its feasibility and efficiency through theoretical analysis. To recycle the memory space due to delete and update operations, we design an efficient move-based garbage collection (GC) mechanism with a novel data layout called virtual coding stripe. Besides, BCStore guarantees consistent data read and write under these new designs, and supports fast online data recovery. We evaluate the performance of BCStore under various workloads. Experimental results show that BCStore can save up to 41% memory compared with replication, and achieve up to 2.4x throughput improvement and 51% bandwidth saving compared to erasure coding with in-place update. © 33rd International Conference on Massive Storage Systems and technology, MSST 2017. All rights reserved.

关键词： Bandwidth

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An Enhanced Computational Feature Selection Method for Medical Synonym Identification via Bilingualism and Multi-corpus Training 2

An Enhanced Computational Feature Selection Method for Medic...

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2017 IEEE 2nd International Conference on Big Data Analysis（ICBDA 2017）

作者： Kai Lei Shangchun Si Desi Wen Ying Shen Institute of Big Data Technologies Shenzhen Key Lab for Cloud Computing Technology and Applications School of Electronic and Computer Engineering(SECE) Peking University

ISBN: (纸本)9781509036202

Medical synonym identification has been an important part of medical natural language processing(NLP).However,in the field of Chinese medical synonym identification,there are problems like low precision and low recall *** solve the problem,in this paper,we propose a method for identifying Chinese medical *** first selected 13 features including Chinese and English *** we studied the synonym identification results of each feature alone and different combinations of the *** the comparison among identification results,we present an optimal combination of features for Chinese medical synonym *** show that our selected features have achieved 97.37% precision rate,96.00% recall rate and 97.33% F1 score.

关键词： medical synonym feature selection bilingual multi-corpus

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Open domain question answering with character-level deep learning models

Open domain question answering with character-level deep lea...

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作者： Lei, Kai Deng, Yang Zhang, Bing Shen, Ying Institute of Big Data Technologies Shenzhen Key Lab for Cloud Computing Technology and Applications School of Electronic and Computer Engineering Peking University Shenzhen518055 China

ISBN: (纸本)9781538636749

Single-relation factoid question answering (QA) is strongly supported by rich sources of facts from knowledge bases (KB). However, there are many irrelevant information in questions and overwhelming number of facts in knowledge bases, making it difficult to capture goal entity and relation involved in a question. In order to settle these issues, firstly, a state-of-the-art sequence tagging model (BiLSTM-CRF) is adopted to detect the entity mention in a question. Then, we propose a n-gram match (NGM) algorithm with Chinese-specific rules and an attention-based siamese bidirectional long-short term memory (ASBLSTM) model to measure the lexical and semantic similarity between questions and candidate facts. Our whole method requires no hand-crafted template or feature engineering. In addition, character-level models are proved to be effective in solving the out of vocabulary (OOV) issue and improving the accuracy in Chinese KBQA task. Experiment results show that our system outperforms the best system with deep learning models in the KBQA share task of the Conference on Natural Language Processing and Chinese computing (NLPCC) 2016 and our system achieves an AverageF1 measure of 80.97% and 37.18% on test dataset in NLPCC 2016 and 2017 respectively. © 2017 IEEE.

关键词： Entity extraction Entity linking Knowledge base question answering Relation recognition

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WordTopic-MultiRank: A New Method for Automatic keyphrase Extraction 6

WordTopic-MultiRank: A New Method for Automatic Keyphrase Ex...

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6th International Joint Conference on Natural Language Processing, IJCNLP 2013

作者： Zhang, Fan Huang, Lian'en Peng, Bo Shenzhen Key Lab for Cloud Computing Technology and Applications Peking University Shenzhen Graduate School Shenzhen518055 China Institute of Network Computing and Information Systems Peking University Beijing100871 China

ISBN: (纸本)9784990734800

Automatic keyphrase extraction aims to pick out a set of terms as a representation of a document without manual assignment efforts. Supervised and unsupervised graph-based ranking methods have been studied for this task. However, previous methods usually computed importance scores of words under the assumption of single relation between words. In this work, we propose WordTopic-MultiRank as a new method for keyphrase extraction, based on the idea that words relate with each other via multiple relations. First we treat various latent topics in documents as heterogeneous relations between words and construct a multi-relational word network. Then, a novel ranking algorithm, named Biased-MultiRank, is applied to score the importance of words and topics simultaneously, as words and topics are considered to have mutual influence on each other. Experimental results on two different data sets show the outstanding performance and robustness of our proposed approach in automatic keyphrase extraction task. © IJCNLP *** right reserved.

关键词： Extraction

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OpenLS-DGF: An Adaptive Open-Source Dataset Generation Framework for Machine Learning Tasks in Logic Synthesis

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IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 2025年

作者： Ni, Liwei Wang, Rui Liu, Miao Meng, Xingyu Lin, Xiaoze Liu, Junfeng Luo, Guojie Chu, Zhufei Qian, Weikang Yang, Xiaoyan Xie, Biwei Li, Xingquan Li, Huawei Chinese Academy of Sciences State Key Lab of Processors Institute of Computing Technology Beijing100190 China Pengcheng Laboratory Shenzhen518055 China University of Chinese Academy of Sciences Beijing101408 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China University of Chinese Academy of Sciences School of Computer Science and Technology Beijing100049 China Peking University School of Computer Science Center for Energy-Efficient Computing and Applications Beijing100871 China Ninbo University Faculty of Electrical Engineering and Computer Science Ninbo315211 China Shanghai Jiao Tong University University of Michigan-Shanghai Jiao Tong University Joint Institute MoE Key Laboratory of Artificial Intelligence Shanghai200240 China Hangzhou Dianzi University School of Electronics and Information Engineering Hangzhou311121 China

This paper introduces OpenLS-DGF, an adaptive logic synthesis dataset generation framework, to enhance machine learning (ML) applications within the logic synthesis process. Previous dataset generation flows were tailored for specific tasks or lacked integrated ML capabilities. While OpenLS-DGF supports various machine learning tasks by encapsulating the three fundamental steps of logic synthesis: Boolean representation, logic optimization, and technology mapping. It preserves the original information in both Verilog and ML-friendly GraphML formats. The Verilog files offer semi-customizable capabilities, enabling researchers to insert additional steps and incrementally refine the generated dataset. Furthermore, OpenLS-DGF includes an adaptive circuit engine that facilitates the final dataset management and downstream tasks. The generated OpenLS-D-v1 dataset comprises 46 combinational designs from established benchmarks, totaling over 966,000 Boolean circuits. OpenLS-D-v1 supports integrating new data features, making it more versatile for new tasks. This paper demonstrates the versatility of OpenLS-D-v1 through four distinct downstream tasks: circuit classification, circuit ranking, quality of results (QoR) prediction, and probability prediction. Each task is chosen to represent essential steps of logic synthesis, and the experimental results show the generated dataset from OpenLSDGF achieves prominent diversity and applicability. The source code and datasets are available at https://***/Logic-Factory/ACE/blob/master/OpenLS-DGF. © 1982-2012 IEEE.

关键词： Information management

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A synchronous algorithm of network coding with hardware logic

A synchronous algorithm of network coding with hardware logi...

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Symposium on ICT and Energy Efficiency and Workshop on Information Theory and Security, CIICT 2012

作者： Li, Jiang Li, Yining Li, Hui Zhu, Zhipu Zhang, Huayu Chen, Fuxing Shenzhen Key Lab. of Cloud Computing Technology and Application Shenzhen Graduate School Peking University Shenzhen 518055 China

ISBN: (纸本)9781849195478

This paper presents an efficient hardware prototype for network coding (NC). First, a packet synchronization mechanism is introduced to settle the problem of packet arriving mismatch between different incoming channels. Then a high-speed lookup-table-based circuit is designed to perform dot product over Galois Field, which forms the basic calculation unit of NC operation. Taking the speed advantage of FPGA hardware, this prototype is able to perform network coding operations within several hundred nanoseconds. Thus further studies and emulations on NC are able to be carried out upon this platform in the real network scenario.

关键词： Network coding

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Query-focused multi-document summarization based on query-sensitive feature space 12

Query-focused multi-document summarization based on query-se...

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21st ACM International Conference on Information and Knowledge Management, CIKM 2012

作者： Yin, Wenpeng Pei, Yulong Zhang, Fan Huang, Lian'en Shenzhen Key Lab. for Cloud Computing Technology and Application Peking University Shenzhen Graduate School Shenzhen 518055 China

ISBN: (纸本)9781450311564

Query-oriented relevance, information richness and novelty are important requirements in query-focused summarization, which, to a considerable extent, determine the summary quality. Previous work either rarely took into account all above demands simultaneously or dealt with part of them in the dynamic process of choosing sentences to generate a summary. In this paper, we propose a novel approach that integrates all these requirements skillfully by treating them as sentence features, making that the finally generated summary could fully reflect the combinational effect of these properties. Experimental results on the DUC2005 and DUC2006 datasets demonstrate the effectiveness of our approach. © 2012 ACM.

关键词： Vector spaces

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Prologue: Unified polymorphic routing towards flexible architecture of reconfigurable infrastructure 9

Prologue: Unified polymorphic routing towards flexible archi...

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9th International ICST Conference on Testbeds and Research Infrastructures for the Development of Networks and Communities, TridentCom 2014

作者： Pan, Kai Li, Hui Liu, Weiyang Zhu, Zhipu Chen, Fuxing Zhu, Bing Shenzhen Engineering Lab of Converged Networks Technology Shenzhen Key Lab of Cloud Computing Technology and Application Peking University Shenzhen Graduate School Shenzhen518055 China

ISBN: (纸本)9783319133256

Today’s Internet architecture was designed and proposed in the 60s and 70s with the intention to interconnect several computing resources across a geographically distributed user group. With the advent of substantially various Internet businesses, traditional Internet is increasingly powerless to satisfy the unprecedented demands. This paper probed the polymorphic routing prototype based on proposed Flexible Architecture of Reconfigurable Infrastructure (FARI) which attempts to emerge as a clean-slate revolution of future Internet and resorts to centralized control manner. Routers in FARI were reconfigurable to adapt to different businesses in terms of identifier type. Moreover, a preliminary framework of FARI is proposed in the end of the article. © Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2014.

关键词： Reconfigurable architectures

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Huge Page Friendly Virtualized Memory Management

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Journal of Computer Science & technology 2020年第2期35卷 433-452页

作者： Sai Sha Jing-Yuan Hu Ying-Wei Luo Xiao-Lin Wang Zhenlin Wang School of Electronics Engineering and Computer Science Peking UniversityBeijing 100871China Peng Cheng Laboratory Shenzhen 518052China Shenzhen Key Laboratory for Cloud Computing Technology&Applications School of Electronic and Computer EngineeringPeking University ShenzhenShenzhen 518000China Department of Computer Science Michigan Technological UniversityMichigan 49246U.S.A.

With the rapid increase of memory consumption by applications running on cloud data centers,we need more efficient memory management in a virtualized *** huge pages becomes more critical for a virtual machine's performance when it runs large working set size *** with large working set sizes are more sensitive to memory allocation,which requires us to quickly adjust the virtual machine's memory to accommodate memory phase *** would be much more efficient if we could adjust virtual machines'memory at the granularity of huge ***,existing virtual machine memory reallocation techniques,such as ballooning,do not support huge *** addition,in order to drive effective memory reallocation,we need to predict the actual memory demand of a virtual *** find that traditional memory demand estimation methods designed for regular pages cannot be simply ported to a system adopting huge *** to adjust the memory of virtual machines timely and effectively according to the periodic change of memory demand is another challenge we *** paper proposes a dynamic huge page based memory balancing system(HPMBS)for efficient memory management in a virtualized *** first rebuild the ballooning mechanism in order to dispatch memory in the granularity of huge *** then design and implement a huge page working set size estimation mechanism which can accurately estimate a virtual machine's memory demand in huge pages *** these two mechanisms,we finally use an algorithm based on dynamic programming to achieve dynamic memory *** show that our system saves memory and improves overall system performance with low overhead.

关键词： virtualization huge page ballooning memory balancing

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A novel biased diversity ranking model for Query-oriented multidocument summarization

A novel biased diversity ranking model for Query-oriented mu...

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2013 International Conference on Vehicle and Mechanical Engineering and Information technology, VMEIT 2013

作者： Lei, Kai Zeng, Yi Fan The Shenzhen Key Lab for Cloud Computing Technology and Application Peking University Shenzhen Graduate School Shenzhen Guangdong 518055 China

ISBN: (纸本)9783037858202

Query-oriented multi-document summarization (QMDS) attempts to generate a concise piece of text byextracting sentences from a target document collection, withthe aim of not only conveying the key content of that corpus,also, satisfying the information needs expressed by that *** to its great applicable value, QMDS has been intensively studied in recent decades. Three properties are supposed crucial for a good summary, i.e., relevance, prestige and low redundancy (orso-called diversity). Unfortunately, most existing work either disregarded the concern of diversity, or handled it with non-optimized heuristics, usually based on greedy sentences election. Inspired by the manifold-ranking process, which deals with query-biased prestige, and DivRank algorithm which captures query-independent diversity ranking, in this paper, we propose a novel biased diversity ranking model, namedManifoldDivRank, for query-sensitive summarization tasks. The top-ranked sentences discovered by our algorithm not only enjoy query-oriented high prestige, more importantly, they are dissimilar with each other. Experimental results on DUC2005and DUC2006 benchmark data sets demonstrate the effectivenessof our proposal. © (2013) Trans Tech Publications, Switzerland.

关键词： Conveying

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