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12th International Asia Pacific Web Conference, APWeb 2010

作者： An, Mingyuan Wang, Yang Wang, Weiping Key Laboratory of Computer System and Architecture Graduate University of Chinese Academy of Sciences Beijing China Key Laboratory of Computer System and Architecture Chinese Academy of Sciences Institute of Computing Technology Beijing China

ISBN: (纸本)9780769540122

MapReduce is a programming framework introduced by Google for large-scale data processing. It is usually used in a scan-centric fashion where all the data are split into blocks and Maps are generated for each block to scan and process the data in the block, then Reduces merge outputs from all the Maps. When a query intends to process only a subset of the data selected by a predicate, this brute-force method may cause extra I/O overhead spent on irrelevant data, and the overhead for initiating so many Maps may be nontrivial given that the actually interesting data for the query is comparatively small in volume. We propose an approach to integrate the index into the MapReduce execution in which only an appropriate number of Maps are generated, each of which accesses the data using an index. This approach incurs random I/O and remote access to data, so the overall performance depends on both system parameters and the query characteristics. We build a cost model for both this index access execution and the traditional full scan execution. This cost model can be used to choose between the two execution modes before executing a query. Experiments show that the index access execution can greatly outperform full scan execution when the selectivity of the predicate is low, and the cost model predicts the actual execution cost very well so can be used to determine the execution plan for a query. © 2010 IEEE.

关键词： MapReduce

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A benchmark test of boson sampling on Tianhe-2 supercomputer

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National Science Review 2018年第5期5卷 715-720页

作者： Junjie Wu Yong Liu Baida Zhang Xianmin Jin Yang Wang Huiquan Wang Xuejun Yang Institute for Quantum Information & State Key Laboratory of High Performance Computing College of ComputerNational University of Defense Technology State Key Laboratory of Advanced Optical Communication Systems and Networks School of Physics and AstronomyShanghai Jiao Tong University Synergetic Innovation Center of Quantum Information and Quantum Physics University of Science and Technology of China

Boson sampling, thought to be intractable classically, can be solved by a quantum machine composed of merely generation, linear evolution and detection of single photons. Such an analog quantum computer for this specific problem provides a shortcut to boost the absolute computing power of quantum computers to beat classical ones. However, the capacity bound of classical computers for simulating boson sampling has not yet been identified. Here we simulate boson sampling on the Tianhe-2 supercomputer, which occupied the first place in the world ranking six times from 2013 to 2016. We computed the permanent of the largest matrix using up to 312 000 CPU cores of Tianhe-2, and inferred from the current most efficient permanent-computing algorithms that an upper bound on the performance of Tianhe-2 is one 50-photon sample per ～100 min. In addition, we found a precision issue with one of two permanent-computing algorithms.

关键词： boson sampling permanent quantum supremacy quantum computing supercomputer

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Hardware Acceleration for SLAM in Mobile Systems

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Journal of computer Science & technology 2023年第6期38卷 1300-1322页

作者：樊哲郝一帆支天郭崎杜子东 State Key Laboratory of Processors Institute of Computing TechnologyChinese Academy of SciencesBeijing 100190China School of Computer Science and Technology University of Chinese Academy of SciencesBeijing 100049China Cambricon Technologies Beijing 100191China

The emerging mobile robot industry has spurred a flurry of interest in solving the simultaneous localization and mapping(SLAM)***,existing SLAM platforms have difficulty in meeting the real-time and low-pow-er requirements imposed by mobile *** specialized hardware is promising with regard to achieving high per-formance and lowering the power,designing an efficient accelerator for SLAM is severely hindered by a wide variety of SLAM *** on our detailed analysis of representative SLAM algorithms,we observe that SLAM algorithms advance two challenges for designing efficient hardware accelerators:the large number of computational primitives and ir-regular control *** address these two challenges,we propose a hardware accelerator that features composable com-putation units classified as the matrix,vector,scalar,and control *** addition,we design a hierarchical instruction set for coping with a broad range of SLAM algorithms with irregular control *** results show that,com-pared against an Intel x86 processor,on average,our accelerator with the area of 7.41 mm^(2) achieves 10.52x and 112.62x better performance and energy savings,respectively,across different *** against a more energy-efficient ARM Cortex processor,our accelerator still achieves 33.03x and 62.64x better performance and energy savings,respec-tively.

关键词： hardware accelerator instruction set mobile system simultaneous localization and mapping(SLAM)algorithm

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Jacobi-Sobolev Orthogonal Polynomialsand Spectral Methods for Elliptic Boundary Value Problems

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Communications on Applied Mathematics and Computation 2019年第2期1卷 283-308页

作者： Xuhong Yu Zhongqing Wang Huiyuan Li University of Shanghai for Science and Technology Shanghai 200093China State Key Laboratory of Computer Science/Laboratory of Parallel Computing Institute of SoftwareChinese Academy of SciencesBeijing 100190China

Generalized Jacobi polynomials with indexes α,β∈ R are introduced and some basic properties are established. As examples of applications,the second- and fourth-order elliptic boundary value problems with Dirichlet or Robin boundary conditions are considered,and the generalized Jacobi spectral schemes are proposed. For the diagonalization of discrete systems,the Jacobi-Sobolev orthogonal basis functions are constructed,which allow the exact solutions and the approximate solutions to be represented in the forms of infinite and truncated Jacobi series. Error estimates are obtained and numerical results are provided to illustrate the effectiveness and the spectral accuracy.

关键词： Generalized Jacobi polynomials Spectral method - Jacobi-Sobolev orthogonal basis functions Elliptic boundary value problems Error analysis

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LMP-GAN: Out-Of-Distribution Detection For Non-Control Data Malware Attacks

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IEEE Transactions on Pattern Analysis and Machine Intelligence 2025年 PP卷 PP页

作者： Wood, David Kapp, David Kebede, Temesgen Hirakawa, Keigo Wuhan University School of Computer Science China Wuhan University National Engineering Research Center for Multimedia Software Hubei Key Laboratory of Multimedia and Network Communication Engineering China Zhongguancun Academy China Wuhan University State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing China Sun Yat-sen University School of Geography and Planning China Mohamed bin Zayed University of Artificial Intelligence United Arab Emirates Chongqing University College of Computer Science China The University of Tokyo Japan RIKEN Center for Advanced Intelligence Project Japan Intelligent Science & Technology Academy Limited CASIC China iFlytek Company Ltd. National Engineering Research Center of Speech and Language Information Processing China Nanyang Technological University College of Computing & Data Science Singapore Henan Academy of Sciences Aerospace Information Research Institute China

Anomaly detection is a common application of machine learning. Out-of-distribution (OOD) detection in particular is a semi-supervised anomaly detection technique where the detection method is trained only on the inlier (in-distribution) samples - unlike the fully supervised variant, the distribution of the outlier samples are never explicitly modeled in OOD detection tasks. In this work, we design a novel GAN-based OOD detection network specifically designed to protect a cyber-physical signal systems from novel Trojan malware called non-control data (NCD) attack that evades conventional malware detection techniques. Inspired in part by the classical locally most powerful (LMP) test in statistical inferences, the proposed LMP-GAN trains the OOD detector (discriminator) by generating OOD samples that are aimed at making maximal alteration to the inlier samples while evading detection. We experimentally compare the results to the state-of-the-art anomaly detection methods to demonstrate the benefits and the appropriateness of the LMP-GAN OOD detector. © 2025 IEEE.

关键词： Malware

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Column-based RLE in row-oriented database

Column-based RLE in row-oriented database

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2009 International Conference on Cyber-Enabled Distributed computing and Knowledge Discovery, CyberC '09

作者： An, Mingyuan Key Laboratory of Computer System and Architecture Institute of Computing Technology Graduate University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781424452187

In database systems, disk I/O performance is usually the bottleneck of the whole query processing. Among many techniques, compression is one of the most important ones to reduce disk accesses so to improve system performance. RLE (Run-Length Encoding) is one light-weight compression algorithm which incurs negligible CPU cost. A lot of work show that, although RLE is one of the most effective compression techniques in column-oriented systems, it is very hard to use due to bad value locality in row-oriented systems where values from multiple attributes are stored in the same page. We propose CRLE (Column-based RLE), one compression algorithm to apply RLE to row-oriented data storage. On row-oriented storage page, CRLE can exploit value locality in individual column and encode values from the same column in run-length format. Experiments show that CRLE can lead to very good compression ratio and performance in spite of row-oriented data storage. © 2009 IEEE.

关键词： Query processing

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Persistent B+-Trees in non-volatile main memory 41st

Persistent B+-Trees in non-volatile main memory

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41st International Conference on Very Large Data Bases, VLDB 2015

作者： Chen, Shimin Jin, Qin State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China Computer Science Department School of Information Renmin University of China China

computer systems in the near future are expected to have Non- Volatile Main Memory (NVMM), enabled by a new generation of Non-Volatile Memory (NVM) technologies, such as Phase Change Memory (PCM), STT-MRAM, and Memristor. The non-volatility property has the promise to persist in-memory data structures for instantaneous failure recovery. However, realizing such promise requires a careful design to ensure that in-memory data structures are in known consistent states after failures. This paper studies persistent in-memory B+-Trees as B+-Trees are widely used in database and data-intensive systems. While traditional techniques, such as undo-redo logging and shadowing, support persistent B+-Trees, we find that they incur drastic performance overhead because of extensive NVM writes and CPU cache flush operations. PCM-friendly B+-Trees with unsorted leaf nodes help mediate this issue, but the remaining overhead is still large. In this paper, we propose write atomic B+-Trees (wB+-Trees), a new type of main-memory B+-Trees, that aim to reduce such overhead as much as possible. wB+-Tree nodes employ a small indirect slot array and/or a bitmap so that most insertions and deletions do not require the movement of index entries. In this way, wB+- Trees can achieve node consistency either through atomic writes in the nodes or by redo-only logging. We model fast NVM using DRAM on a real machine and model PCM using a cycle-accurate simulator. Experimental results show that compared with previous persistent B+-Tree solutions, wB+-Trees achieve up to 8.8x speedups on DRAM-like fast NVM and up to 27.1x speedups on PCM for insertions and deletions while maintaining good search performance. Moreover, we replaced Memcached's internal hash index with tree indices. Our real machine Memcached experiments show that wB+-Trees achieve up to 3.8X improvements over previous persistent tree structures with undo-redo logging or shadowing. © 2015 VLDB Endowment 21508097/15/03.

关键词： Dynamic random access storage

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Microblog Sentiment Analysis with Emoticon Space Model

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Journal of computer Science & technology 2015年第5期30卷 1120-1129页

作者：姜飞刘奕群栾焕博孙甲申朱璇张敏马少平 State Key Laboratory of Intelligent Technology and Systems Beijing 100084 China Tsinghua National Laboratory for Information Science and Technology Beijing 100084 China Department of Computer Science and Technology Tsinghua University Beijing 100084 China Language Computing Laboratory Samsung Research & Development Institute of China Beijing 100028 China

Emoticons have been widely employed to express different types of moods, emotions, and feelings in microblog environments. They are therefore regarded as one of the most important signals for microblog sentiment analysis. Most existing studies use several emoticons that convey clear emotional meanings as noisy sentiment labels or similar sentiment indicators. However, in practical microblog environments, tens or even hundreds of emoticons are frequently adopted and all emoticons have their own unique emotional meanings. Besides, a considerable number of emoticons do not have clear emotional meanings. An improved sentiment analysis model should not overlook these phenomena. Instead of manually assigning sentiment labels to several emoticons that convey relatively clear meanings, we propose the emoticon space model （ESM） that leverages more emotieons to construct word representations from a massive amount of unlabeled data. By projecting words and microblog posts into an emoticon space, the proposed model helps identify subjectivity, polarity, and emotion in microblog environments. The experimental results for a public microblog benchmark corpus （NLP＆CC 2013） indicate that ESM effectively leverages emoticon signals best runs. and outperforms previous state-of-the-art strategies and benchmark

关键词： microblog sentiment analysis emoticon space polarity classification subjectivity classification emotion clas-sification

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Communication Lower Bounds of Convolutions in CNNs 20

Communication Lower Bounds of Convolutions in CNNs

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32nd ACM Symposium on Parallelism in Algorithms and architectures, SPAA 2020

作者： Zhang, Xiaoyang Xiao, Junmin Tan, Guangming State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Science Beijing China

ISBN: (纸本)9781450369350

Convolution is the most time-consuming part in the computation of convolutional neural networks (CNNs). Due to the complex data dependency and the increase in the amount of model samples, the convolution suffers from high overhead on data movement. This work provides comprehensive analysis and methodologies to minimize the communication for the convolutions in CNNs. With an in-depth analysis on the I/O complexity theory under the red-blue pebble game model, we develop a general communication lower bound theory for a composite algorithm which consists of several different sub-computations. Based on the proposed theory, we establish the data movement lower bound results for three main convolution algorithms in CNNs, which are the direct convolution, the image2col method and Winograd algorithm. Furthermore, derived from I/O lower bound results, we design the near communication-optimal strategies respectively for the three main convolution algorithms by fully exploiting the data reuse. The deep analysis demonstrates that our designs are able to nearly reach the minimum communication in a two-level memory hierarchy. © 2020 Owner/Author.

关键词： Convolution

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RSAK: Random stream attack for phase change memory in video applications

RSAK: Random stream attack for phase change memory in video ...

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2013 IEEE 31st VLSI Test Symposium, VTS 2013

作者： Fang, Yuntan Li, Huawei Li, Xiaowei State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781467355438

As an emerging non-volatile memory technology, phase change memory (PCM) is promising as an alternative for traditional memories such as DRAM. In spite of its non-volatility, high density, low standby power, and resilience to soft errors, PCM has a limited write endurance or lifetime, which means that each PCM cell can only be overwritten finite times. More importantly, limited lifetime potentially provides malicious attackers an opportunity to intentionally aggravate write traffic into PCM. In this paper, from the standpoint of attackers, we propose random stream attacks (RSAK) methods for phase change memory used in video applications. Experimental results show that compared to natural video sequences, RSAK incurs higher total write traffic or worsened lifetime. RSAK also gives hints on how to build a more secure PCM in video applications to counter malicious write streams. © 2013 IEEE.

关键词： Phase change memory

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