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The influences of model parameters on the characteristics of memristors

Chinese Physics B 2012年第4期21卷 576-585页

作者：周静黄达 National Laboratory for Parallel and Distributed Processing School of ComputerNational University of Defense TechnologyChangsha 410073China

As the fourth passive circuit component, a memristor is a nonlinear resistor that can ＂remember＂ the amount of charge passing through it. The characteristic of ＂remembering＂ the charge and non-volatility makes memristors great potential candidates in many fields. Nowadays, only a few groups have the ability to fabricate memristors, and most researchers study them by theoretic analysis and simulation. In this paper, we first analyse the theoretical base and characteristics of memristors, then use a simulation program with integrated circuit emphasis as our tool to simulate the theoretical model of memristors and change the parameters in the model to see the influence of each parameter on the characteristics. Our work supplies researchers engaged in memristor-based circuits with advice on how to choose the proper parameters.

关键词： memristor I-V characteristics simulation program with integrated circuit emphasis

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NR-MPI: A Non-stop and Fault Resilient MPI

NR-MPI: A Non-stop and Fault Resilient MPI

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International Conference on parallel and distributed Systems (ICPADS)

作者： Guang Suo Yutong Lu Xiangke Liao Min Xie Hongjia Cao State Key Laboratory of High Performance Computing National University of Defense Technology Changsha Hunan Province China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha Hunan Province China

Fault resilience has became a major issue for HPC systems, in particular in the perspective of future E-scale systems, which will consist of millions of CPU cores and other components. Fault tolerant MPI was proposed to offer support of software level fault tolerance approaches. However, the widely used MPI implementations, such as MPICH and Mvapich2, provide limited support for fault tolerance. This paper proposes NR-MPI, a Non-stop and Fault Resilient MPI. NR-MPI implements the semantics of FT-MPI based on MPICH. Specifically, this paper focuses on failure detection in MPI library, online failure recovery of communicators for multiple failures, friendly programming interface extending for NR-MPI. Furthermore, to support failure recovery of applications, NR-MPI implements data backup and restore interfaces based on double in-memory checkpoint/restart. We conduct experiments with NPB benchmarks on TH-1A supercomputer. Experimental results show that NR-MPI based fault tolerant programs can recover from failures online without restarting, and the overhead is small even for applications with tens of thousands of cores.

关键词： Fault tolerance Fault tolerant systems Libraries Resource management Context Programming Semantics

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Latency-Aware Dynamic Voltage and Frequency Scaling on Many-Core Architectures for Data-Intensive Applications

Latency-Aware Dynamic Voltage and Frequency Scaling on Many-...

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International Conference on Cloud Computing and Big Data (CloudCom-Asia)

作者： Zhiquan Lai King Tin Lam Cho-Li Wang Jinshu Su Youliang Yan Wangbin Zhu National University of Defense Technology China The University of Hong Kong Hong Kong National Key Laboratory of Parallel and Distributed Processing (PDL) China Huawei Technologies Co. Ltd. Shenzhen China

Low power is the first-class design requirement for HPC systems. Dynamic voltage and frequency scaling (DVFS) has become the commonly used and efficient technology to achieve a trade-off between power consumption and system performance. However, most the prior work using DVFS did not take into account the latency of voltage/frequency scaling, which is a critical factor in real hardware determining the power efficiency of the power management algorithm. This paper, firstly, investigate the latency features of DVFS on a real many-core hardware platform. Secondly, we propose a latency-aware DVFS algorithm for profile-based power management to avoid aggressive power state transitions. At last, we evaluate our algorithm on Intel SCC platform using a data-intensive benchmark, Graph 500 benchmark. The experimental results not only show impressive potential for energy saving in data-intensive applications (up to 31% energy saving and 60% EDP reduction), but also evaluate the efficiency of our latency-aware DVFS algorithm which achieves 12.0% extra energy saving and 5.0% extra EDP reduction, moreover, increases the execution performance by 22.4%.

关键词： Benchmark testing Runtime Hardware Heuristic algorithms Time-frequency analysis Voltage measurement

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A fast successive over-relaxation algorithm for force-directed network graph drawing

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Science China(Information Sciences) 2012年第3期55卷 677-688页

作者： WANG YongXian & WANG ZhengHua national key laboratory for parallel and distributed processing, national University of Defense Technology, Changsha 410073, China 1. National Key Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha 410073 China

Force-directed approach is one of the most widely used methods in graph drawing research. There are two main problems with the traditional force-directed algorithms. First, there is no mature theory to ensure the convergence of iteration sequence used in the algorithm and further, it is hard to estimate the rate of convergence even if the convergence is satisfied. Second, the running time cost is increased intolerablely in drawing largescale graphs, and therefore the advantages of the force-directed approach are limited in practice. This paper is focused on these problems and presents a sufficient condition for ensuring the convergence of iterations. We then develop a practical heuristic algorithm for speeding up the iteration in force-directed approach using a successive over-relaxation (SOR) strategy. The results of computational tests on the several benchmark graph datasets used widely in graph drawing research show that our algorithm can dramatically improve the performance of force-directed approach by decreasing both the number of iterations and running time, and is 1.5 times faster than the latter on average.

关键词： graph drawing graph layout successive over-relaxation force-directed algorithm

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Efficiently indexing sparse wide tablesin cloud computing

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Information Technology Journal 2013年第20期12卷 5415-5423页

作者： Huang, Bin Peng, Yuxing Department of Computer Huaihua University 418008 Huaihua China School of Computer Science Wuhan University 430072 Wuhan China National Laboratory of Parallel and Distributed Processing National University of Defense Technology 410073 Changsha China

For its perception of unlimited resources and infinite scalability, Cloud Computing has emerged as a pervasive paradigm for hosting? data-centric applications in large computing infrastructures. The data produced by these applications are essentially sparse and wide and may change schema frequently, traditional relational data model is inappropriate for their data management. A new data model, called Sparse Wide Table, was introduced for this task. Unfortunately, we have to face many challenges in building the secondary index for Sparse Wide Table in cloud, as the distributed and column-oriented storage which eliminates a number of NULLs. In this study, we present a three-level index scheme for efficient data processing in the Cloud. Our approach can be summarized as follows. First, we build an index for each column by which the records can be rebuilt easily. Second, we build a bitmap index for each storage node which only indexes the data residing on the node. Third, we organize the storage nodes as a structured overlay and each node maintains a portion of the global index for the all different data. The global index is a bitmap index to indicate the node each data resides in. Finally, based on the three-level index scheme, some query algorithms are implemented. We conduct extensive experiments on a LAN and the results demonstrate that our indexing scheme is dynamic, efficient and scalable. © 2013 Asian Network for Scientific Information.

关键词： Cloud computing

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A distributed algorithm for SI transactions serializability in cloud computing

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Information Technology Journal 2013年第24期12卷 8435-8445页

作者： Huang, Bin Peng, Yuxing Peng, Xiaoning School of Computer Science Wuhan University Wuhan 430072 China Department of Computer Huaihua University Huaihua 418008 China National Laboratory of Parallel and Distributed Processing National University of Defense Technology Changsha 410073 China

There are well known anomalies permitted by snapshot isolation that can lead to violations of data consistency by interleaving transactions that individually maintain consistency. Until now, there are some ways to prevent these anomalies only in single computer and there are not the corresponding solving methods in cloud computing. This paper describes our PDCC algorithm to detect cycles in a snapshot isolation dependency graph and abort transactions to break the cycle in cloud computing. The algorithm ensures serializable executions for SI transactions in cloud computing. Based on the transaction concurrency control of Percolator, we have implemented our algorithm in an open source cloud database system (HBase) and our performance study shows that PDCC throughput and scalability are good. © 2013 Asian Network for Scientific Information.

关键词： Cloud computing

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Mining Software Profile across Multiple Repositories for Hierarchical Categorization

Mining Software Profile across Multiple Repositories for Hie...

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International Conference on Software Maintenance (ICSM)

作者： Tao Wang Huaimin Wang Gang Yin Charles X. Ling Xiang Li Peng Zou National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China Department of Computer Science The University of Western Ontario London Ontario Canada Academy of Equipment Beijing China

ISBN: (纸本)9781467352185

The large amounts of software repositories over the Internet are fundamentally changing the traditional paradigms of software maintenance. Efficient categorization of the massive projects for retrieving the relevant software in these repositories is of vital importance for Internet-based maintenance tasks such as solution searching, best practices learning and so on. Many previous works have been conducted on software categorization by mining source code or byte code, which are only verified on relatively small collections of projects with coarse-grained categories or clusters. However, Internet-based software maintenance requires finer-grained, more scalable and language-independent categorization approaches. In this paper, we propose a novel approach to hierarchically categorize software projects based on their online profiles across multiple repositories. We design a SVM-based categorization framework to classify the massive number of software hierarchically. To improve the categorization performance, we aggregate different types of profile attributes from multiple repositories and design a weighted combination strategy which assigns greater weights to more important attributes. Extensive experiments are carried out on more than 18,000 projects across three repositories. The results show that our approach achieves significant improvements by using weighted combination, and the overall precision, recall and F-Measure can reach 71.41%, 65.60% and 68.38% in appropriate settings. Compared to the previous work, our approach presents competitive results with 123 finer-grained and multi-layered categories. In contrast to those using source code or byte code, our approach is more effective for large-scale and language-independent software categorization.

关键词： Databases Collaboration Servers Software maintenance Internet Data mining

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Orthogonal Nonnegative Locally Linear Embedding

Orthogonal Nonnegative Locally Linear Embedding

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IEEE International Conference on Systems, Man, and Cybernetics

作者： Lei Wei Naiyang Guan Xiang Zhang Zhigang Luo Dacheng Tao National Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha 410073 P.R. China These authors contributed equally to this paper National Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha 410073 P.R. China Centre for Quantum Computation and Intelligence Systems and Faculty of Engineering and Information Technology University of Technology Sydney Sydney NSW 2007 Australia

ISBN: (纸本)9781479906505

Nonnegative matrix factorization (NMF) decomposes a nonnegative dataset X into two low-rank nonnegative factor matrices, i.e., W and H, by minimizing either Kullback-Leibler (KL) divergence or Euclidean distance between X and WH. NMF has been widely used in pattern recognition, data mining and computer vision because the non-negativity constraints on both W and H usually yield intuitive parts-based representation. However, NMF suffers from two problems: 1) it ignores geometric structure of dataset, and 2) it does not explicitly guarantee partsbased representation on any datasets. In this paper, we propose an orthogonal nonnegative locally linear embedding (ONLLE) method to overcome aforementioned problems. ONLLE assumes that each example embeds in its nearest neighbors and keeps such relationship in the learned subspace to preserve geometric structure of a dataset. For the purpose of learning parts-based representation, ONLLE explicitly incorporates an orthogonality constraint on the learned basis to keep its spatial locality. To optimize ONLLE, we applied an efficient fast gradient descent (FGD) method on Stiefel manifold which accelerates the popular multiplicative update rule (MUR). The experimental results on real-world datasets show that FGD converges much faster than MUR. To evaluate the effectiveness of ONLLE, we conduct both face recognition and image clustering on real-world datasets by comparing with the representative NMF methods.

关键词： Nonnegative matrix factorization Locally linear embedding Fast gradient descent Stiefel manifold Dataset Nonnegative matrix decomposition geometrical construction NMF protocol images embedding Flue gas desulfurization Nearest neighbor Orthogonal

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MPtostream:an OpenMP compiler for CPU-GPU heterogeneous parallel systems

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Science China(Information Sciences) 2012年第9期55卷 1961-1971页

作者： YANG XueJun,TANG Tao ,WANG GuiBin,JIA Jia & XU XinHai national laboratory for parallel and distributed processing,national University of Defense Technology,Changsha 410073,China 1. National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha 410073 China

In light of GPUs’ powerful floating-point operation capacity,heterogeneous parallel systems incorporating general purpose CPUs and GPUs have become a highlight in the research field of high performance computing(HPC).However,due to the complexity of programming on GPUs,porting a large number of existing scientific computing applications to the heterogeneous parallel systems remains a big *** OpenMP programming interface is widely adopted on multi-core CPUs in the field of scientific *** effectively inherit existing OpenMP applications and reduce the transplant cost,we extend OpenMP with a group of compiler directives,which explicitly divide tasks among the CPU and the GPU,and map time-consuming computing fragments to run on the GPU,thus dramatically simplifying the *** have designed and implemented MPtoStream,a compiler of the extended OpenMP for AMD’s stream processing *** experimental results show that programming with the extended directives deviates from programming with OpenMP by less than 11% modification and achieves significant speedup ranging from 3.1 to 17.3 on a heterogeneous system,incorporating an Intel Xeon E5405 CPU and an AMD FireStream 9250 GPU,over the execution on the Xeon CPU alone.

关键词： GPGPU stream OpenMP compiler

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SPICE modeling of memristors with multilevel resistance states

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Chinese Physics B 2012年第9期21卷 594-600页

作者：方旭东唐玉华吴俊杰 National Laboratory for Parallel and Distributed Processing School of ComputerNational University of Defense Technology Department of Computer Science and Technology School of ComputerNational University of Defense Technology

With CMOS technologies approaching the scaling ceiling, novel memory technologies have thrived in recent years, among which the memristor is a rather promising candidate for future resistive memory （RRAM）. Memristor＇s potential to store multiple bits of information as different resistance levels allows its application in multilevel cell （MCL） tech- nology, which can significantly increase the memory capacity. However, most existing memristor models are built for binary or continuous memristance switching. In this paper, we propose the simulation program with integrated circuits emphasis （SPICE） modeling of charge-controlled and flux-controlled memristors with multilevel resistance states based on the memristance versus state map. In our model, the memristance switches abruptly between neighboring resistance states. The proposed model allows users to easily set the number of the resistance levels as parameters, and provides the predictability of resistance switching time if the input current/voltage waveform is given. The functionality of our models has been validated in HSPICE. The models can be used in multilevel RRAM modeling as well as in artificial neural network simulations.

关键词： memristor multilevel cell SPICE model

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