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检索条件"主题词=partitioning algorithms"

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A Novel Approach to Quantum Circuit partitioning

A Novel Approach to Quantum Circuit Partitioning

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IEEE-Computer-Society Annual Symposium on VLSI (ISVLSI)

作者： Clark, Joseph Thapliyal, Himanshu Humble, Travis S. Univ Tennessee Knoxville TN 37996 USA Oak Ridge Natl Lab Oak Ridge TN USA

ISBN: (数字)9781665466059

ISBN: (纸本)9781665466059

Quantum synthesis presents an effective method of circuit optimization, but scales exponentially with the number of qubits in the circuit. This problem can be addressed by partitioning the circuit into blocks with a limited number of qubits. Existing partitioning algorithms make large trade-offs to achieve either high speed or quality. We propose a method of circuit partitioning which is competitive with existing algorithms for both metrics. The proposed method is compared with two existing methods across common circuit architectures, matching an exhaustive solution in performance and a fast solution on time.

关键词： Measurement Circuit optimization Qubit Computer architecture Very large scale integration partitioning algorithms Quantum circuit

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Relational Data partitioning using Evolutionary Game Theory 5

Relational Data Partitioning using Evolutionary Game Theory

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IEEE Symposium on Computational Intelligence and Data Mining (CIDM)

作者： Hall, Lawrence O. Chakeri, Alireza Univ S Florida Dept Comp Sci & Engn Tampa FL 33620 USA

ISBN: (纸本)9781479945184

This paper presents a new approach for relational data partitioning using the notion of dominant sets. A dominant set is a subset of data points satisfying the constraints of internal homogeneity and external in-homogeneity, i.e. a cluster. However, since any subset of a dominant set cannot be a dominant set itself, dominant sets tend to be compact sets. Hence, in this paper, we present a novel approach to enumerate well distributed clusters where the number of clusters need not be known. When the number of clusters is known, in order to search the solution space appropriately, after finding each dominant set, data points are partitioned into two disjoint subsets of data points using spectral graph image segmentation methods to enumerate the other well distributed dominant sets. For the latter case, we introduce a new hierarchical approach for relational data partitioning using a new class of evolutionary game theory dynamics called InImDynamics which is very fast and linear, in computational time, with the number of data points. In this regard, at each level of the proposed hierarchy, Dunn's index is used to find the appropriate number of clusters. Then the objects are partitioned based on the projected number of clusters using game theoretic relations. The same method is applied to each partition to extract its underlying structure. Although the resulting clusters exist in their equivalent partitions, they may not be clusters of the entire data. Hence, they are checked for being an actual cluster and if they are not, they are extended to an existing cluster of the data. The approach can also be used to assign unseen data to existing clusters, as well.

关键词： evolutionary computation game theory graph theory image segmentation pattern clustering set theory Dunn's index InImDynamics data cluster data point partitioning dominant sets evolutionary game theory dynamics external in-homogeneity hierarchical approach internal homogeneity object partitioning relational data partitioning spectral graph image segmentation methods Clustering algorithms Games Indexes Nash equilibrium partitioning algorithms Vectors Game theory partitioning algorithms Set Theory Clustering algorithms image segmentation evolutionary algorithm Data partitioning Nash equilibrium Graph theory Cluster Analysis Clusters

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Optimal Online Balanced Graph partitioning 40

Optimal Online Balanced Graph Partitioning

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40th IEEE Conference on Computer Communications (IEEE INFOCOM)

作者： Pacut, Maciej Parham, Mahmoud Schmid, Stefan Univ Vienna Fac Comp Sci Vienna Austria

ISBN: (纸本)9780738112817

Distributed applications generate a significant amount of network traffic. By collocating frequently communicating nodes (e.g., virtual machines) on the same clusters (e.g., server or rack), we can reduce the network load and improve application performance. However, the communication pattern of different applications is often unknown a priori and may change over time, hence it needs to be learned in an online manner. This paper revisits the online balanced partitioning problem that asks for an algorithm that strikes an optimal tradeoff between the benefits of collocation (i.e., lower network load) and its costs (i.e., migrations). Our first contribution is a significantly improved deterministic lower bound of Omega(k . l) on the competitive ratio, where l is the number of clusters and k is the cluster size, even for a scenario in which the communication pattern is static and can be perfectly partitioned;we also provide an asymptotically tight upper bound of O (k . l) for this scenario. For k = 3, we contribute an asymptotically tight upper bound of Theta(l) for the general model in which the communication pattern can change arbitrarily over time. We improve the result for k = 2 by providing a strictly 6-competitive upper bound for the general model.

关键词： Upper bound Computational modeling Conferences Clustering algorithms Telecommunication traffic Virtual machining partitioning algorithms

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Reducing Positioning Errors in the Important Access Point Selection Method for Fingerprint Localization by Spatial partitioning 31

Reducing Positioning Errors in the Important Access Point Se...

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31st International Conference on Information Networking (ICOIN)

作者： Kim, HaeSung Hwang, Dong Yeop Kim, Ki-Hyung Jung, Jai-Jin Ajou Univ Dept Comp Engn Suwon Gyeonggi Do South Korea Dept Cyber Secur Seoul South Korea Dankook Univ Dept Multimedia Engn Yongin Gyeonggi Do South Korea

ISBN: (纸本)9781509051243

Recently, as the interest of location based services has increased, research on indoor positioning technology has been actively conducted. In particular, methods on fingerprinting that is less affected by obstacles has become a promising approach. In this paper, we propose a method to reduce positioning errors in the important access point selection method for fingerprint localization by spatial partitioning.

关键词： Position measurement partitioning algorithms Computer aided software engineering Clustering algorithms Measurement uncertainty Mobile radio mobility management

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Improving the static analysis of loops by dynamic partitioning techniques 3

Improving the static analysis of loops by dynamic partitioni...

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3rd IEEE International Workshop on Source Code Analysis and Manipulation

作者： Martel, M CEA LIST DTSI SLA F-91191 Gif Sur Yvette France

ISBN: (纸本)0769520057

Many static analyses aim at assigning to each control point of a program an invariant property that characterizes any state of a trace corresponding to this point. The choice of the set of control points determines the states of an execution trace for which a common property must be found. In this article, we focus on sufficient conditions to substitute one control flow graph for another during an analysis. Next, we introduce a dynamic partitioning algorithm that improves the precision of the calculated invariants by deciding dynamically how to map the states of the traces to the control points, depending on the properties resulting from the first steps of the analysis. In particular this algorithm enables the loops to be unfolded only if this improves the precision of the final invariants. Its correctness stems from the fact that it uses legal graph substitutions.

关键词： Algorithm design and analysis Assembly Conferences Flow graphs Heuristic algorithms Law Legal factors Merging partitioning algorithms Sufficient conditions

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Efficient Hardware/Software partitioning for Heterogeneous Embedded Systems

Efficient Hardware/Software partitioning for Heterogeneous E...

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IEEE International Conference on the Science of Electrical Engineering in Israel (ICSEE)

作者： Manor, Erez Greenberg, Shlomo Ben Gurion Univ Negev Dept Elect & Comp Engn Beer Sheva Israel

ISBN: (纸本)9781538663783

This paper presents a novel model-based hardware/software co-design methodology applied to heterogeneous embedded platforms. A time-predictable hardware and software co-design architecture design is proposed. The proposed technique is based on floating point operations analysis and is intended to be applied for real-time applications at an early stage of the design, to assist the designer taking the right considerations in choosing the most effective Hardware/Software partitioning. The design analysis is carried out on the MATLAB model of the application, and is demonstrated for a specific voice activation algorithm. A Data Flow Graph (DFG) representation is used to represent the various operational blocks of the chosen algorithm. An efficient decomposition of the design operational blocks into a fixed software processor and alternative extensible hardware components is carefully carried out to find the correct balance between flexibility and performance with respect to power consumption and size, and the demands related to time predictability. Experimental results demonstrate that the proposed algorithm performs a significant area saving factor of 39% and power consumption reduction of 19%, while applied to voice activation module within the same system constraints.

关键词： Task analysis Hardware Software partitioning algorithms Mathematical model Computer architecture Matlab

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FDPrior: A Force-Directed Based Parallel partitioning Algorithm for Three Dimensional Integrated Circuits on GPGPU

FDPrior: A Force-Directed Based Parallel Partitioning Algori...

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International Symposium on VLSI Design, Automation and Test (VLSI-DAT)

作者： Chen, Wan-Jing Kuo, Hsien-Kai Chiu, Tsou-Han Lai, Bo-Cheng Charles Natl Chiao Tung Univ Dept Elect Engn Hsinchu 30010 Taiwan

ISBN: (纸本)9781424484997

This paper proposes an innovative force-directed parallel algorithm, FDPrior, to solve the multilayer partitioning problem of 3DICs. The growing scale and multi-layered structure of the 3DIC technology make it computational expensive for EDA tools to achieve optimization goals. Exploiting the algorithmic parallelism on multi-core architectures becomes the key to attain scalable runtime. By adopting the N-body simulation scheme and novel techniques to reduce synchronization overhead, FDPrior successfully exposes the massive parallelism on the multi-core GPGPU architecture. The objective is to minimize the total number of Through Silicon Vias (TSVs) while meeting the area constraint for each layer. The experimental results on ISPD98 benchmark show that FDPrior outperforms the conventional FM algorithm by achieving in average 5.0X better TSVs and up to 247.3X runtime speedup. Compared with PP3D, a parallel 3DIC partitioning algorithm, FDPrior achieves 6.7X better TSVS with 3.3 X runtime enhancement.

关键词： 3D IC technology EDA tools FDPrior Force Frequency modulation GPGPU Mobile communication N-body simulation scheme Optimization Parallel processing partitioning algorithms Runtime computer graphic equipment coprocessors force-directed based parallel partitioning algorithm general purpose graphic processing unit multicore architectures multilayer partitioning problem synchronization overhead reduction three dimensional integrated circuits three-dimensional integrated circuits through silicon vias

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A Novel Bayesian Network based Scheme for Finding the Optimal Solution to Stochastic Online Equi-partitioning Problems 13

A Novel Bayesian Network based Scheme for Finding the <i>Opt...

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13th International Conference on Machine Learning and Applications (ICMLA)

作者： Glimsdal, Sondre Granmo, Ole-Christoffer Univ Agder Dept ICT Grimstad Norway

ISBN: (纸本)9781479974153

A number of intriguing decision scenarios, such as order picking, revolve around partitioning a collection of objects so as to optimize some application specific objective function. In its general form, this problem is referred to as the Object partitioning Problem (OOP), known to be NP-hard. We here consider a variant of OPP, namely the Stochastic Online Equi-partitioning Problem (SO-EPP). In SO-EPP, objects arrive sequentially, in pairs. The relationship between the arriving object pairs is stochastic: They belong to the same partition with probability p. From a history of object arrivals, the goal is to predict which objects will appear together in future arrivals. As an additional complication, the partitions of related objects are required to be of equal cardinality. The decision maker, however, is not informed about the true relation between the objects, he is merely observing the stream of object pairs, and has to predict future behavior. Inferring the correct partitioning from historical behavior is thus a significant challenge, which becomes even more difficult when p is unknown. Previously, only heuristic sub-optimal solution strategies have been proposed for SO-EPP. In this paper, we propose the first optimal solution strategy. In brief, the scheme that we propose, BN-EPP, is founded on a Bayesian Network representation of SO-EPP problems. Based on probabilistic reasoning we are not only able to infer the correct object partitioning with optimal accuracy. We are also able to simultaneously infer p, allowing us to accelerate learning as object pairs arrive. Being optimal, BN-EPP provides superior performance compared to existing state-of-the-art solution schemes. BN-EPP is also highly flexible, being capable of encoding object partitioning constraints. Finally, BN-EPP is parameter free - its performance does not rely on fine tuning any parameters. As a result of these advantages, BN-EPP opens up for significantly improved performance for OOP based applicat

关键词： belief networks inference mechanisms optimisation BN-EPP Bayesian network representation NP-hard problem OOP SO-EPP novel Bayesian network based scheme object partitioning problem probabilistic reasoning stochastic online equi-partitioning problems Bayes methods Convergence Meteorology Noise partitioning algorithms Probabilistic logic Stochastic processes Bayesian networks object oriented programming Soft computing Nondeterministic polynomial-time hard partitioning algorithms Probabilistic logic Inference mechanisms Bayes methods Markov chain Meteorology Converge Noise

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Challenges and pitfalls of partitioning blockchains 48

Challenges and pitfalls of partitioning blockchains

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48th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W)

作者： Fynn, Enrique Pedone, Fernando Univ Svizzera Italiana Lugano Switzerland

ISBN: (纸本)9781538665534

Blockchain has received much attention in recent years. This immense popularity has raised a number of concerns, scalability of blockchain systems being a common one. In this paper, we seek to understand how Ethereum, a well-established blockchain system, would respond to sharding. Sharding is a prevalent technique to increase the scalability of distributed systems. To understand how sharding would affect Ethereum, we model Ethereum blockchain as a graph and evaluate five methods to partition the graph. We assess methods using three metrics: the balance among shards, the number of transactions that would involve multiple shards, and the amount of data that would be relocated across shards upon repartitioning of the graph.

关键词： Contracts Bitcoin partitioning algorithms Scalability Measurement

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Sensor Network partitioning based on Homogeneity

Sensor Network Partitioning based on Homogeneity

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Proceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics (IEEE DSAA 2015)

作者： Xu, Yi Zhang, Zhongfei Zhang, Yaqing Yu, Philip S. Binghamton Univ Dept Comp Sci Binghamton NY USA Zhejiang Univ Coll Informat Sci & Elect Engn Hangzhou Zhejiang Peoples R China Univ Illinois Dept Comp Sci Chicago IL USA

ISBN: (纸本)9781467382731

Discovering communities from sensor networks is an important problem in many real-world applications. The problem desiderata requires to partition the network according to the homogeneity of the sensor measurement and at the same time the partitioning result to be as independent as possible of the typical local change in the network topology. This poses new challenges to the current graph partitioning methodologies. We develop a graph partitioning approach from the perspective of homogeneity. In order to avoid the inherent incompatibility of the current graph partitioning methodologies, an objective functional is designed to be asymptotically close to the Mumford-Shah functional [1]. An variational algorithm ZERO-CUT and a fast approximation algorithm GREEDY-SACK are developed to solve the objective functional. We evaluate the performance of the proposed algorithms on both synthetic and real-world graphs in different applications to demonstrate its advantage and promise in solving the problem of discovering communities from sensor networks.

关键词： Approximation algorithms Approximation methods Area measurement Layout Network topology partitioning algorithms Topology Network topology area measurement partitioning algorithms Approximation algorithms Approximation method layouts topology homogeneity Sensor networks partitions

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