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Asian Test Symposium (ATS)

作者： Jing Ye Xiaolin Zhang Yu Hu Xiaowei Li Chinese Academy and Sciences Beijing China Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy and Sciences Beijing China Chinese Academy of Sciences Beijing Beijing CN

Volume diagnosis plays an important role in the yield learning process. To get a high quality diagnosis result, patterns with high distinguish ability are essential. However, the test patterns used by volume diagnosis commonly have low distinguish ability to specific faults. In our experiments, we observe that on average, under automatic generated test patterns, faults in the same fan out free region (FFR) account for only 6% of all possible fault pairs, but their share in total indistinguishable faults is 70%, faults in different FFRs but with the same observation points account for 4% of all fault pairs, but their share in total indistinguishable faults is 22%. Exploiting this fact that faults in the same FFRs are harder to be distinguished, we propose an Automatic Diagnostic Pattern Generation (ADPG) method named Substantial Fault Pairs at-A-Time (SFPAT)-ADPG. By applying a transformed circuit and a new fault list to an existing Automatic Test Pattern Generation (ATPG) tool, we generate the compressed test patterns which are also the diagnostic patterns with high distinguish ability for the original circuit. Experiments on ISCAS'89 and ITC'99 benchmark circuits show the effectiveness of the proposed SFPAT-ADPG method.

关键词： Circuit faults Automatic test pattern generation Benchmark testing Logic gates Transforms Integrated circuit modeling

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Design of Low-Cost High-Performance Floating-Point Fused Multiply-Add with Reduced Power

Design of Low-Cost High-Performance Floating-Point Fused Mul...

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International Conference on VLSI Design

作者： Zichu Qi Qi Guo Ge Zhang Xiangku Li Weiwu Hu Chinese Academy and Sciences Beijing China Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy and Sciences Beijing China Chinese Academy of Sciences Beijing Beijing CN

ISBN: (纸本)9781424455416

This paper presents a floating-point fused multiply-add (FMA) unit with low-cost and low power techniques. To improve the performance, two single-precision operations can be performed concurrently with one double-precision datapath, which is very useful in multimedia and even scientific applications. Moreover, to reduce the additional area costs for supporting two single-precision operations in parallel, multiple double-precision units, i.e., the multiplier, shifter and adder, are reused as much as possible. A modified dual-path algorithm is proposed by classifying the exponent difference into three cases and implementing them with close and far paths, which can reduce latency and facilitate lowering power consumption by enabling only one of the two paths. In addition, in case of FADD instructions, the multiplier in the first stage is bypassed and kept in stable mode, which can significantly improve FADD instruction performance and lower power consumption. The overall FMA unit has a latency of 4 cycles while the FADD operation has 3 cycles. Each cycle has a time delay of about 0.66 ns in the ST 65 nm CMOS technology. Compared with the conventional double-precision FMA, about 13% delay is reduced and about 22% area is increased, which is acceptable since two single-precision results can be generated simultaneously.

关键词： Costs Energy consumption CMOS technology Hardware Throughput Very large scale integration Laboratories computer architecture Delay effects Roundoff errors

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Improved asymptotic multicast throughput for random extended networks

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computer Communications 2010年第18期33卷 2195-2202页

作者： Cheng Wang Changjun Jiang Xiang-Yang Li Jiujun Cheng Department of Computer Science and Technology Tongji University Shanghai China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications China Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai China Department of Computer Science Illinois Institute of Technology Chicago IL 60616 USA

We study the asymptotic throughput for random extended networks , where n ad hoc nodes are randomly deployed in a square region R ( n ) = 0 , n 2 . We directly consider the multicast throughput to unify the unicast and broadcast throughput, and design a new multicast scheme under the generalized physical model based on the so-called secondary highways system . Taking account of all possible cases of n s = ω (1) and 1 ⩽ n d ⩽ n − 1, we derive the achievable multicast throughput, where n s and n d denote the number of sessions and the number of destinations of each session. We prove that for some cases in terms of n s and n d , our scheme achieves better throughput than the existing schemes.

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Protein classification using family profiles

Protein classification using family profiles

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： YuGang Li Yao Lu Fa Zhang ZhenGe Qiu ZhiYong Liu Beijing Key Laboratory of Intelligence Information Technology School of Computer Science & Technology Beijing Institute of Technology Beijing China Institute of Computing Technology Chinese Academy and Sciences Beijing China

Protein classification plays an important role in the research in Bioinformatics. Many discriminative methods, including the SVM based algorithms are used to do this job. In order to use these methods, variable length protein sequences must be converted into fixed-length dimensional vectors. The current work presents a new method of converting sequences into vectors. The method first constructs profile sequences for each protein domain family, then the alignment values of every family profile sequence with a single protein sequence, is used as the protein's according vectors. Then classification algorithms are used to train and predict protein sequences involved. Experiments were presented to test the ability of the SVM algorithm and the LS_StaticEField algorithm to recognize previously unknown sequences via this converting method. Experimental results show that the converting method is good enough and that the LS_StaticEField algorithm is comparable with the SVM one.

关键词： Proteins Classification algorithms Support vector machines Hidden Markov models Kernel Training

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Godson-T:An Efficient Many-Core architecture for Parallel Program Executions

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Journal of computer Science & technology 2009年第6期24卷 1061-1073页

作者：范东睿袁楠张军超周永彬林伟宋风龙叶笑春黄河余磊龙国平张浩刘磊 Key Laboratory of Computer Systems and Architecture Institute of Computing Technology Chinese Academy of Sciences

Moore＇s law will grant computer architects ever more transistors for the foreseeable future, and the challenge is how to use them to deliver efficient performance and flexible programmability. We propose a many-core architecture, Godson- T, to attack this challenge. On the one hand, Godson-T features a region-based cache coherence protocol, asynchronous data transfer agents and hardware-supported synchronization mechanisms, to provide full potential for the high efficiency of the on-chip resource utilization. On the other hand, Godson-T features a highly efficient runtime system, a Pthreadslike programming model, and versatile parallel libraries, which make this many-core design flexibly programmable. This hardware/software cooperating design methodology bridges the high-end computing with mass programmers. Experimental evaluations are conducted on a cycle-accurate simulator of Godson-T. The results show that the proposed architecture has good scalability, fast synchronization, high computational efficiency, and flexible programmability.

关键词： many-core parallel computing multithread data communication thread synchronization runtime system

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Axiomatic Temporal Logic Programs Verification

Axiomatic Temporal Logic Programs Verification

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Theoretical Aspects of Software Engineering (TASE)

作者： Xiaoxiao Yang Zhenhua Duan Institute of Computing Theory & Technology and ISN Laboratory Xidian University Xi'an China State Key Laboratory of Computer Science Institute of Software Chinese Academy and Sciences China

In this paper, we investigate the axiomatic system of Modeling Simulation and Verification Language (MSVL). To this end, a set of state axioms and state inference rules is given. They are useful to deduce a program into its normal form. Further, a propositional projection temporal logic is used as assertion language to describe the required property of a program. Moreover, to deduce a program over an interval, a set of rules in terms of triple like Hoare logic is formalized. These rules enable us to deduce a program in its normal form at the current state to the next one and to verify safety, liveness properties over an interval.

关键词： Semantics Writing Logic programming Computational modeling Laboratories Software

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Preservative translations between logical systems

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作者： Shen, Yuming Ma, Yue Cao, Cungen Sui, Yuefei Wang, Ju Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences 100190 China Graduate University of Chinese Academy of Sciences 100049 China School of Computer Science and Information Engineering Guangxi Normal University 541004 China

ISBN: (纸本)3642163262

This paper investigates a subclass of translations between logical systems, called the preservative translations, which preserve the satisfiability and the unsatisfiability of formulas. The definition of preservative translation is given and connections between the preservative translation and other definitions of translations in the literature are discussed. Some properties of logical systems, such as the compactness and the decidability, which are characterized by the existence of preservative translations between logical systems are also studied. © 2010 IFIP.

关键词： Artificial intelligence

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An improved bp neural network algorithm based on factor analysis

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Journal of Convergence Information technology 2010年第4期5卷

作者： Ding, Shifei Jia, Weikuan Su, Chunyang Liu, Xiaoliang Chen, Jinrong School of Computer Science and Technology China University of Mining and Technology Xuzhou 221116 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China

Back-Propagation (BP) neural network, as one of the most mature and most widespread algorithms, has the ability of large scale computing and has unique advantages when dealing with nonlinear high dimensional data. But when we manipulate high dimensional data with BP neural network, many feature variables provide enough information, but too many network inputs go against designing of the hidden-layer of the network and take up plenty of storage space as well as computing time, and in the process interfere the convergence of the training network, even influence the the accuracy of recognition finally. Factor analysis (FA) is a multivariate analysis method which transforms many feature variables into few synthetic variables. Aiming at the characteristics that the samples processed have more feature variables, combining with the structure feature of BP neural network, a FA-BP neural network algorithm is proposed. Firstly we reduce the dimensionality of the feature factor using FA, and then regard the features reduced as the input of the BP neural network, carry on network training and simulation with low dimensional data that we get. This algorithm here can simplify the network structure, improve the velocity of convergence, and save the running time. Then we apply the new algorithm in the field of pest prediction to emulate. The results show that under the prediction precision is not reduced, the error of the prediction value is reduced by using the new algorithm, and therefore the algorithm is effective.

关键词： Neural networks

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Using genetic algorithms to optimize artificial neural networks

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Journal of Convergence Information technology 2010年第8期5卷 6-6页

作者： Ding, Shifei Xu, Li Su, Chunyang Zhu, Hong School of Computer Science and Technology China University of Mining and Technology Xuzhou 221116 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China

Artificial Neural Networks (ANNs), as a nonlinear and adaptive information processing systems, play an important role in machine learning, artificial intelligence, and data mining. But the performance of ANNs is sensitive to the number of neurons, and chieving a better network performance and simplifying the network topology are two competing objectives. While Genetic Algorithms (GAs) is a kind of random search algorithm which simulates the nature selection and evolution, which has the advantages of good global search abilities and learning the approximate optimal solution without the gradient information of the error functions. This paper makes a brief survey on ANNs optimization with GAs. Firstly, the basic principles of ANNs and GAs are introduced, by analyzing the advantages and disadvantages of GAs and ANNs, the superiority of using GAs to optimize ANNs is expressed. Secondly, we make a brief survey on the basic theories and algorithms of optimizing the network weights, optimizing the network architecture and optimizing the learning rules, and make a discussion on the latest research progresses. At last, we make a prospect on the development trend of the theory.

关键词： Genetic algorithms

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A novel ant colony genetic hybrid algorithm

Journal of Software

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Journal of Software 2010年第11期5卷 1179-1186页

作者： Gao, Shang Zhang, Zaiyue Cao, Cungen School of Computer Science and Technology Jiangsu University of Science and Technology Zhenjiang 212003 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China

By use of the properties of ant colony algorithm and genetic algorithm, a novel ant colony genetic hybrid algorithm, whose framework of hybrid algorithm is genetic algorithm, is proposed to solve the traveling salesman problems. The selection operator is an artificial version of natural selection, and chromosomes with better length of tour have higher probabilities of being selected in the next generation. Based on the properties of pheromone in ant colony algorithm the ant colony crossover operation is given. Four mutation strategies are put forward using the characteristic of traveling salesman problems. The hybrid algorithm with 2-opt local search can effectively find better minimum beyond premature convergence. Ants choose several tours based on trail, and these tours will replace the worse solution. Compare with the simulated annealing algorithm, the standard genetic algorithm and the standard ant colony algorithm, all the 4 hybrid algorithms are proved effective. Especially the hybrid algorithm with strategy D is a simple and effective better algorithm than others. © 2010 ACADEMY PUBLISHER.

关键词： Genetic algorithms

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