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检索条件"主题词=partitioning algorithms"

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Fast graph partitioning algorithms

Fast graph partitioning algorithms

引用

IEEE Pacific Rim Conference on Communications, Computers and Signal Processing

作者： M.S. Khan K.F. Li Department of Electrical and Computer Engineering University of Victoria Victoria BC Canada

The following k-way graph partitioning (GP) problem is considered: given an undirected weighted graph G(V,E), partition the nodes of G into k parts of almost equal size such that the partition-cost (sum of the weights on edges with nodes in different parts) is minimized. Two simple and fast algorithms are proposed, namely, direct algorithm AUCTION and iterative algorithm GREEDYCYCLE. In algorithm AUCTION, the idea of using auction and biddings is introduced using the master-workers paradigm. Algorithm GREEDYCYCLE is a greedy algorithm where the idea of cyclic node passing among parts during the iterative improvement stage is introduced. Cyclic node passing is a k-way generalization of the 2-way node exchange found in the Kernighan-Lin (1970) approach. Experimental results show that, as compared to the existing algorithms, these algorithms are extremely fast, and they produce solutions of reasonable quality.

关键词： partitioning algorithms Iterative algorithms Greedy algorithms Very large scale integration Circuits Costs Scholarships Iterative methods Annealing Broadcasting

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Heuristic software partitioning algorithms for distributed real-time applications

Heuristic software partitioning algorithms for distributed r...

引用

International Conference on Software Engineering (ICSE)

作者： H. Xin Z. Hong C. Xiyao Dept. of Comput. Sci. Northwest Telecommun. Eng. Inst. Xian China Department of Computer Science Northwest Telecommunications Engineering Institute Xi'an China

ISBN: (纸本)0897912586

The authors deal with the problems of software partition for distributed real-time applications. The software-partitioning models analyzed are those that take maximizing the efficiency in resource utilization for their objective, while observing the constraints on CPU throughput, memory space available, maximally allowed task execution time, and the order of module execution. The problem of software partition based on the models is proved to be NP-complete. There is no efficient partitioning algorithm for the models. The authors present two heuristic software-partitioning algorithms.< >

关键词： Heuristic algorithms partitioning algorithms Software algorithms Application software Resource management Real time systems Costs Software performance Delay Throughput

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Process variation-aware workload partitioning algorithms for GPUs supporting spatial-multitasking 14

Process variation-aware workload partitioning algorithms for...

引用

Design, Automation and Test in Europe Conference and Exhibition

作者： Paula Aguilera Jungseob Lee Amin Farmahini-Farahani Katherine Morrow Michael Schulte Nam Sung Kim University of Wisconsin Madison Advanced Micro Devices

ISBN: (纸本)9783981537024

High-level programming languages have transformed graphics processing units (GPUs) from domain-restricted devices into powerful compute platforms. Yet many “generalpurpose GPU” (GPGPU) applications fail to fully utilize the GPU resources. Executing multiple applications simultaneously on different regions of the GPU (spatial multitasking) thus improves system performance. However, within-die process variations lead to significantly different maximum operating frequencies (F max ) of the streaming multiprocessors (SMs) within a GPU. As the chip size and number of SMs per chip increase, the frequency variation is also expected to increase, exacerbating the problem. The increased number of SMs also provides a unique opportunity: we can allocate resources to concurrently-executing applications based on how those applications are affected by the different available F max values. In this paper, we study the effects of per-SM clocking on spatial multitasking-capable GPUs. We demonstrate two factors that affect the performance of simultaneously-running applications: (i) the SM partitioning algorithm that decides how many resources to assign to each application, and (ii) the assignment of SMs to applications based on the operating frequencies of those SMs and the applications characteristics. Our experimental results show that spatial multitasking that partitions SMs based on application characteristics, when combined with per-SM clocking, can greatly improve application performance by up to 46% on average compared to cooperative multitasking with global clocking.

关键词： Graphics processing units Multitasking Clocks Business process re-engineering partitioning algorithms Kernel Frequency control

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DFG partitioning algorithms for Coarse Grained Reconfigurable Array Assisted RTL Simulation Accelerators

DFG Partitioning Algorithms for Coarse Grained Reconfigurabl...

引用

IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)

作者： Ipsita Biswas Mahapatra Utkarsh Agarwal S. K. Nandy CAD Lab Indian Institute of Science Bangalore India Adobe Systems Bangalore India

As the complexity of circuit design increases, verification of these circuits through simulation also becomes extremely challenging. This creates a bottleneck in the IC design process. Distributed simulation is one way of solving this problem where the simulation workload is distributed among the parallel processors involved in the simulation. However the design has to be carefully partitioned for this purpose. In order to perform distributed simulation, many efficient partitioning algorithms have been proposed till date. These algorithms mostly partition gate level netlist or logic circuits and reduces inter-processor communication by minimizing cutsize for a given constraint of load balance. In this paper, we present two different partitioning schemes for performing distributed simulation. They are: a Discrete Particle Swarm optimization (DPSO) based partitioning algorithm (DPSO-PA) and an effective partitioning heuristic. These algorithms partitions Data Flow Graph (DFG) for a recently proposed Coarse Grained Reconfigurable Array assisted Hardware Accelerator (CGRA-HA). We also propose an improved version of the original DPSO methodology through careful selection of initial partition sets. It is found that the proposed heuristic based partitioning algorithm outperforms the modified DPSO-PA in terms of lesser cut-edges.

关键词： partitioning algorithms Integrated circuit modeling Load modeling Logic gates Sociology Statistics Hardware design languages

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Survey of data partitioning algorithms for big data stores

Survey of data partitioning algorithms for big data stores

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International Conference on Parallel Distributed and Grid Computing (PDGC)

作者： Shraddha Phansalkar Swati Ahirrao Symbiosis Institute of Technology Symbiosis International University Pune India

ISBN: (纸本)9781509036707

Data partitioning plays an important role in distributed systems to elevate performance of the applications. Big data applications require the augmented metrics of performance like responsiveness, availability, scalability and throughput. Data partitioning across multiple nodes improves the performance of the application with respect to its scalability and throughput. Although there is a rich literature on the data partitioning algorithms in distributed systems for big data applications, there is a need to classify as well as regroup the algorithms based on their strategies. The paper presents an exhaustive classification of data partitioning algorithms based on their strategies as well as operational units. A survey of this kind gives an insight to the user about not only a comparative analysis of performance of approaches but also suggests suitability of these approaches for candidate big data applications.

关键词： partitioning algorithms Clustering algorithms Big Data applications Distributed databases Algorithm design and analysis Cost function

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Improving performance of mobile cloud applications using application partitioning algorithms

Improving performance of mobile cloud applications using app...

引用

International Conference on Global Trends in Signal Processing, Information Computing and Communication (ICGTSPICC)

作者： Dipika S. Diwase Department of Computer Engineering SSGMCE Shegaon India

Cloud computing is a very important feature in which application resources are provided over the internet as a service to users that discovering its utilization all over. Mobile Cloud Computing (MCC) combines the features of mobile computing and cloud computing for improving performance. Mobile computing and cloud computing technologies has drastically changed the current perspective on distributed computing. In mobile cloud computing, programmer offloads the entire application from mobile devices to computational clouds where applications are partitioned at different levels of granularity for distributed application processing. Application partitioning is used to separate the intensive components of the mobile applications which operate independently in the distributed processing environment. In this paper, we will discuss computational offloading process of resources to cloud and different application partitioning algorithms for offloading in mobile cloud computing. Here, we give a review of application partitioning schemes in mobile cloud computing highlighting important features and key issues in this area. In this paper, we also discuss about challenges in partitioning of elastic application selecting appropriate research domains and exploring technique of distributed application processing in MCC that offering more data reliability.

关键词： Cloud computing partitioning algorithms Mobile communication Mobile handsets Algorithm design and analysis Computational modeling Mobile computing

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An experimental evaluation of partitioning algorithms

An experimental evaluation of partitioning algorithms

引用

Annual IEEE International Conference and Exhibit ASIC

作者： C.-W. Yeh C.-K. Cheng T.-T.Y. Lin University of California San Diego CA USA

Presents an experimental evaluation of partitioning algorithms to supplement the work done by D.S. Johnson, et al. (1989). MCNC test-cases are used as part of the test beds. A two-level partitioning algorithm is proposed whose performance exceeds that of the algorithm by C.M. Fiduccia, R.M. Mattheyses (1982) on real circuitry by as much as 28%.< >

关键词： partitioning algorithms Simulated annealing Circuit testing Circuit simulation Macrocell networks Timing Benchmark testing Signal design Joining processes Geometry

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Predictive Evaluation of partitioning algorithms through Runtime Modelling

Predictive Evaluation of Partitioning Algorithms through Run...

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International Conference on High Performance Computing

作者： R. A. Bunt S. A. Wright S. A. Jarvis Y. K. Ho M. J. Street Department of Computer Science University of Warwick Coventry United Kingdom Design Systems Engineering Rolls-Royce plc Derby United Kingdom

ISBN: (纸本)9781509054121

Performance modelling unstructured mesh codes is a challenging process, due to the difficulty of capturing their memory access patterns, and their communication patterns at varying scale. In this paper we first develop extensions to an existing runtime performance model, aimed at overcoming the former, which we validate on up to 1,024 cores of a Haswellbased cluster, using both a geometric partitioning algorithm and ParMETIS to partition the input deck, with a maximum absolute runtime error of 12.63% and 11.55% respectively. To overcome the latter, we develop an application representative of the mesh partitioning process internal to an unstructured mesh code. This application is able to generate partitioning data that is usable with the performance model to produce predicted application runtimes within 7.31% of those produced using empirically collected data. We then demonstrate the use of the performance model by undertaking a predictive comparison among several partitioning algorithms on up to 30,000 cores. Additionally, we correctly predict the ineffectiveness of the geometric partitioning algorithm at 512 and 1024 cores.

关键词： Runtime Computational modeling Data models Predictive models partitioning algorithms Prediction algorithms Analytical models

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New faster Kernighan-Lin-type graph-partitioning algorithms 93

New faster Kernighan-Lin-type graph-partitioning algorithms

引用

IEEE International Conference on Computer-Aided Design

作者： S. Dutt Department of Electrical Engineering University of Minnesota Minneapolis MN USA

ISBN: (纸本)9780818644900

In this paper we present a very efficient graph partitioning scheme QuickCut that uses the basic strategy of the Kernighan-Lin (K-L) algorithm to swap pairs of nodes to improve an existing partition of a graph G. The main feature of QuickCut is a "neighborhood search" strategy that is based on the result (obtained in this paper) that it is not necessary to search more than a certain subset of d/sup 2/ node pairs to find the node pair with the maximum swap gain. Here d is the maximum node degree of G. We also use an improved data structure, viz., balanced trees, to store the nodes in the two partitions. Due to the new search strategy and data structure, QuickCut has a worst-case time complexity of /spl Theta/(max(ed, e log n)), and an average-case complexity of /spl Theta/(e log n), where e is the number of edges of G. The K-L algorithm, on the other hand, has a time complexity of /spl Theta/(n/sup 2/ log n), where n is the number of nodes of G. Another contribution of this paper is the presentation of efficient node-pair scanning methods for obtaining the best node pair to swap in the K-L algorithm. We have implemented QuickCut, K-L, and its various enhancements suggested here. The results obtained from using these different algorithms to partition a number of random and other well-defined graphs show that QuickCut is the fastest, and that it is faster than the K-L algorithm by factors of 5 to 50. Thus QuickCut can serve as the basis for very fast VLSI partitioning and layout tools.

关键词： Subspace constraints partitioning algorithms Circuits Very large scale integration Wires Costs Tree data structures Wiring Simulated annealing Genetic algorithms

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Coupling-aware graph partitioning algorithms: Preliminary study

Coupling-aware graph partitioning algorithms: Preliminary st...

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International Conference on High Performance Computing

作者： Maria Predari Aurélien Esnard Univ. Bordeaux LaBRI Talence France CNRS LaBRI Talence France

In the field of scientific computing, load balancing is a major issue that determines the performance of parallel applications. Nowadays, simulations of real-life problems are becoming more and more complex, involving numerous coupled codes, representing different models. In this context, reaching high performance can be a great challenge. In this paper, we present graph partitioning techniques, called co-partitioning, that address the problem of load balancing for two coupled codes: the key idea is to perform a “coupling-aware” partitioning, instead of partitioning these codes independently, as it is usually done. Finally, we present a preliminary experimental study which compares our methods against the usual approach.

关键词： Couplings Program processors Computational modeling partitioning algorithms Load modeling Load management Atmospheric modeling

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