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A novel application of parallel betweenness centrality to power grid contingency analysis

A novel application of parallel betweenness centrality to po...

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24th ieee International parallel and distributed processing symposium, IPDPS 2010

作者： Jin, Shuangshuang Huang, Zhenyu Chen, Yousu Chavarría-Miranda, Daniel Feo, John Wong, Pak Chung Pacific Northwest National Laboratory Richland WA 99354 United States

ISBN: (纸本)9781424464432

In Energy Management Systems, contingency analysis is commonly performed for identifying and mitigating potentially harmful power grid component failures. The exponentially increasing combinatorial number of failure modes imposes a significant computational burden for massive contingency analysis. It is critical to select a limited set of high- impact contingency cases within the constraint of computing power and time requirements to make it possible for real-time power system vulnerability assessment. In this paper, we present a novel application of parallel betweenness centrality to power grid contingency selection. We cross-validate the proposed method using the model and data of the western US power grid, and implement it on a Cray XMT system - a massively multithreaded architecture - leveraging its advantages for parallel execution of irregular algorithms, such as graph analysis. We achieve a speedup of 55 times (on 64 processors) compared against the single-processor version of the same code running on the Cray XMT. We also compare an OpenMP-based version of the same code running on an HP Superdome shared-memory machine. The performance of the Cray XMT code shows better scalability and resource utilization, and shorter execution time for large-scale power grids. This proposed approach has been evaluated in PNNL's Electricity Infrastructure Operations Center (EIOC). It is expected to provide a quick and efficient solution to massive contingency selection problems to help power grid operators to identify and mitigate potential widespread cascading power grid failures in real time. © 2010 ieee.

关键词： parallel processing systems

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Power-efficientwork distribution method for CPU-GPU heterogeneous system

Power-efficientwork distribution method for CPU-GPU heteroge...

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ieee International symposium on parallel and distributed processing With Applications

作者： Wang, Guibin Ren, Xiaoguang National Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology Changsha Hunan China

ISBN: (纸本)9780769541907

As the system scales up continuously, the problem of power consumption for high performance computing (HPC) system becomes more severe. Heterogeneous system integrating two or more kinds of processors, could be better adapted to heterogeneity in applications and provide much higher energy efficiency in theory. Many studies have shown heterogeneous system is preferable on energy consumption to homogeneous system in a multi-programmed computing environment. However, how to exploit energy efficiency (Flops/Watt) of heterogeneous system for a single application or even for a single phase in an application has not been well studied. This paper proposes a power-efficient work distribution method for single application on a CPU-GPU heterogeneous system. The proposed method could coordinate inter-processor work distribution and per-processor's frequency scaling to minimize energy consumption under a given scheduling length constraint. We conduct our experiment on a real system, which equips with a multi-core CPU and a multi-threaded GPU. Experimental results show that, with reasonably distributing work over CPU and GPU, the method achieves 14% reduction in energy consumption than static mappings for several typical benchmarks. We also demonstrate that our method could adapt to changes in scheduling length constraint and hardware configurations. © 2010 ieee.

关键词： Graphics processing unit

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Automation and management of scientificworkflows in distributed network environments

Automation and management of scientificworkflows in distribu...

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2010 ieee International symposium on parallel and distributed processing, Workshops and Phd Forum, IPDPSW 2010

作者： Wu, Qishi Zhu, Mengxia Lu, Xukang Brown, Patrick Lin, Yunyue Gu, Yi Cao, Fei Reuter, Michael A. Department of Computer Science University of Memphis Memphis TN 38152 United States Department of Computer Science Southern Illinois University Carbondale IL 62901 United States Oak Ridge National Laboratory Neutron Science Scattering Division Oak Ridge TN 37831 United States

ISBN: (纸本)9781424465347

Large-scale computation-intensive applications in various science fields feature complex DAG-structured workflows comprised of distributed computing modules with intricate inter-module dependencies. Supporting such workflows in heterogeneous network environments and optimizing their end-to-end performance are crucial to the success of large-scale collaborative scientific applications. We design and develop a generic Scientific Workflow Automation and Management Platform (SWAMP), which contains a set of easy-to-use computing and networking toolkits for application scientists to conveniently assemble, execute, monitor, and control complex computing workflows in distributed network environments. The current version of SWAMP integrates the graphical user interface of Kepler to compose abstract workflows and employs Condor DAGMan for workflow dispatch and execution. SWAMP provides a web-based user interface to automate and manage workflow executions and uses a special workflow mapper to optimize the end-to-end workflow performance. A case study of the workflow for Spallation Neutron Source datasets in real networks is presented to show the efficacy of the proposed platform.

关键词： Workflow management

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Balls into non-uniform bins

Balls into non-uniform bins

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24th ieee International parallel and distributed processing symposium, IPDPS 2010

作者： Berenbrink, Petra Brinkmann, André Friedetzky, Tom Nagel, Lars School of Computing Science Simon Fraser University Burnaby BC V5A 1S6 Canada Paderborn Center for Parallel Computing University of Paderborn 33102 Paderborn Germany School of Engineering and Computing Sciences Durham University Durham DH1 3LE United Kingdom

ISBN: (纸本)9781424464432

Balls-into-bins games for uniform bins are widely used to model randomized load balancing strategies. Recently, balls-into-bins games have been analysed under the assumption that the selection probabilities for bins are not uniformly distributed. These new models are motivated by properties of many peer-to-peer (P2P) networks, which are not able to perfectly balance the load over the bins. While previous evaluations try to find strategies for uniform bins under nonuniform bin selection probabilities, this paper investigates heterogeneous bins, where the "capacities" of the bins might differ significantly. We show that heterogeneous environments can even help to distribute the load more evenly, and that the load difference between bins can be bounded by O(log log n) if each ball has two random choices, where n is the number of bins. Our analysis and simulation results show, for the first time, that the maximum load in heterogeneous balls-into-bins games is independent from the overall system capacity C and that bigger bins therefore can help to achieve good load balancing properties. © 2010 ieee.

关键词： Peer to peer networks

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A tile-based parallel viterbi algorithm for biological sequence alignment on GPU with CUDA

A tile-based parallel viterbi algorithm for biological seque...

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2010 ieee International symposium on parallel and distributed processing, Workshops and Phd Forum, IPDPSW 2010

作者： Du, Zhihui Yin, Zhaoming Bader, David A. Department of Computer Science and Technology Tsinghua National Laboratory for Information Science and Technology Tsinghua University 100084 Beijing China School of Software and Microelectronics Peking University 100871 China Georgia Institute of Technology College of Computing Atlanta GA 30332 United States

ISBN: (纸本)9781424465347

The Viterbi algorithm is the compute-intensive kernel in Hidden Markov Model (HMM) based sequence alignment applications. In this paper, we investigate extending several parallel methods, such as the wave-front and streaming methods for the Smith-Waterman algorithm, to achieve a significant speed-up on a GPU. The wave-front method can take advantage of the computing power of the GPU but it cannot handle long sequences because of the physical GPU memory limit. On the other hand, the streaming method can process long sequences but with increased overhead due to the increased data transmission between CPU and GPU. To further improve the performance on GPU, we propose a new tile-based parallel algorithm. We take advantage of the homological segments to divide long sequences into many short pieces and each piece pair (tile) can be fully held in the GPU's memory. By reorganizing the computational kernel of the Viterbi algorithm, the basic computing unit can be divided into two parts: independent and dependent parts. All of the independent parts are executed with a balanced load in an optimized coalesced memory-accessing manner, which significantly improves the Viterbi algorithm's performance on GPU. The experimental results show that our new tile-based parallel Viterbi algorithm can outperform the wave-front and the streaming methods. Especially for the long sequence alignment problem, the best performance of tile-based algorithm is on average about an order magnitude faster than the serial Viterbi algorithm. © 2010 ieee.

关键词： Graphics processing unit

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Towards realistic networks for simulating large-scale distributed systems

Towards realistic networks for simulating large-scale distri...

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ieee International symposium on parallel and distributed processing With Applications

作者： Sun, Yibo Bahulkar, Ketan Kim, Dai-Hee Zhydkov, Dmytro Chiu, Kenneth Department of Computer Science State University of New York at Binghamton P.O. Box 6000 Binghamton NY 13902 United States

ISBN: (纸本)9780769541907

Research in large-scale distributed systems, such as P2P systems, often relies critically on simulations to validate research results. Though systems such as PlanetLab [15] can be used to test on real networks in some cases, there are still significant practical challenges to evaluating large-scale distributed systems on actual hardware. Actual measured datasets such as the ones measured with King's method [1] also have an important role, but often do not provide enough scale or are not representative of the network for which the research is intended. Typically, in such cases, tools such as GT-ITM [4] are used to generate network topologies for the evaluation simulation. These tools work reasonably well at generating physical topologies that are representative of real systems. The behavior of distributed systems, however, depends not just on the physical topologies, but also the routing policies and other factors that affect latency and bandwidth. These aspects may have a considerable impact on any evaluation performed on the generated network, and can lead to significant differences between simulated performance and actual performance. In particular, triangle inequality violations and path inflation can adversely impact large-scale distributed systems. In this paper, we present techniques and approaches for adding such real-world effects to generated networks, in a parametrized approach. We show the parameters can be varied to generate a variety of networks with different characteristics, and compare them to measured datasets. © 2010 ieee.

关键词： Network topology

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Error-correcting codes for concurrent error correction in bit-parallel systolic and scalable multipliers for shifted dual basis of GF(2m)

Error-correcting codes for concurrent error correction in bi...

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ieee International symposium on parallel and distributed processing With Applications

作者： Lee, Chiou-Yng Department of Computer Information and Network Engineering Lunghwa University of Science and Technology Taiwan

ISBN: (纸本)9780769541907

This work presents a novel bit-parallel systolic multiplier for the shifted dual basis of GF(2m). The shifted dual basis multiplication for all trinomials can be represented as the sum of two Hankel matrix-vector multiplications. The proposed multiplier architecture comprises one Hankel multiplier and one (2m-1)-bit adder. The algebraic encoding scheme based on linear cyclic codes is adopted to implement the multiplications with concurrent error correction (CEC). The latency overhead is analytically demonstrated to require extra four clock cycles than as compared by the multiplier without CEC. The block Hankel matrix-vector representation is used to derive a CEC scalable SDB multiplier. In the binary field GF(284), the space overhead of the proposed bit-parallel architecture using cyclic code is around 22.8%. The proposed CEC scalable multiplier given by seven or fewer injection errors can correct nearly 99.6% of error correction. Unlike the existing concurrent error detection multipliers that apply the parity prediction scheme, the proposed architectures have multiple error-detection capabilities. © 2010 ieee.

关键词： Error correction

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Using solid angles to detect protein docking regions by CUDA parallel algorithms

Using solid angles to detect protein docking regions by CUDA...

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ieee International symposium on parallel and distributed processing With Applications

作者： Lo, Ying-Tsang Tsai, Yueh-Lin Wang, Hsin-Wei Hsu, Yu-Ping Pai, Tun-Wen Department of Computer Science and Engineering National Taiwan Ocean University Keelung Taiwan Center for Marine Bioenvironment and Biotechnology National Taiwan Ocean University Keelung Taiwan

ISBN: (纸本)9780769541907

A novel approach based on solid angles and CUDA parallel technologies for detection of protein docking regions is proposed in this paper. A key feature of a solid angle reveals the geometrical characteristics of protein surface structures and provides an efficient criterion for identifying the anchor amino acids on surface regions. These solid angles as well as several corresponding physical properties facilitate rapid evaluation on matching shape complementary from two interactive proteins. According to the performance of the proposed algorithms on enzyme-inhibitor protein complexes, the retrieved and clustered potential docking regions and the counterpart of centralized anchor amino acids can be effectively determined. Most of identified candidate regions on protein surfaces reveal either with concave or convex characteristics, and the results conform to the regular conditions of protein docking phenomena with respect to enzyme-inhibitor complexes. More importantly, the main goal of this paper not only identifies possible protein docking regions by evaluating solid angle characteristics, but also provides a feasible and efficient way to identify possible binding regions by employing the CUDA parallel computing architecture. The system evaluation has shown that the proposed algorithms achieved an accuracy rate of 62.85% for identifying possible docking regions on two interacted proteins and an average of one-half saving in running time requirements by incorporating CUDA parallel algorithms. © 2010 ieee.

关键词： parallel algorithms

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parallel computation of best connections in public transportation networks

Parallel computation of best connections in public transport...

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24th ieee International parallel and distributed processing symposium, IPDPS 2010

作者： Delling, Daniel Katz, Bastian Pajor, Thomas Microsoft Research Silicon Valley 1065 La Avenida Mountain View CA 94043 United States Department of Computer Science Karlsruhe Institute of Technology 76128 Karlsruhe Germany

ISBN: (纸本)9781424464432

Exploiting parallelism in route planning algorithms is a challenging algorithmic problem with obvious applications in mobile navigation and timetable information systems. In this work, we present a novel algorithm for the so- called one-to-all profile-search problem in public transportation networks. It answers the question for all fastest connections between a given station S and any other station at any time of the day in a single query. This algorithm allows for a very natural parallelization, yielding excellent speed- ups on standard multi-core servers. Our approach exploits the facts that first, time-dependent travel-time functions in such networks can be represented as a special class of piecewise linear functions, and that second, only few connections from S are useful to travel far away. Introducing the connection- setting property, we are able to extend DlJKSTRA's algorithm in a sound manner. Furthermore, we also accelerate station-to- station queries by preprocessing important connections within the public transportation network. As a result, we are able to compute all relevant connections between two random stations in a complete public transportation network of a big city (Los Angeles) on a standard multi-core server in less than 55 ms on average. © 2010 ieee.

关键词： Travel time

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A distributed diffusive heuristic for clustering a virtual P2P supercomputer

A distributed diffusive heuristic for clustering a virtual P...

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2010 ieee International symposium on parallel and distributed processing, Workshops and Phd Forum, IPDPSW 2010

作者： Gehweiler, Joachim Meyerhenke, Henning Department of Computer Science University of Paderborn Fürstenallee 11 D-33102 Paderborn Germany

ISBN: (纸本)9781424465347

For the management of a virtual P2P supercomputer one is interested in subgroups of processors that can communicate with each other efficiently. The task of finding these subgroups can be formulated as a graph clustering problem, where clusters are vertex subsets that are densely connected within themselves, but sparsely connected to each other. Due to resource constraints, clustering using global knowledge (i. e., knowing (nearly) the whole input graph) might not be permissible in a P2P scenario, e. g., because collecting the data is not possible or would consume a high amount of resources. That is why we present a distributed heuristic using only limited local knowledge for clustering static and dynamic graphs. Based on disturbed diffusion, our algorithm DIDIC implicitly optimizes cut-related quality measures such as modularity. It thus settles between distributed clustering algorithms for other quality measures (e. g., energy efficiency in the field of ad-hoc-networking) and graph clustering algorithms optimizing cut-related measures with global knowledge. Our experiments with graphs resembling a virtual P2P supercomputer show the promising potential of the new approach: Although each node starts with a random cluster number, may communicate only with its direct neighbors within the graph, and requires only a small amount of additional memory space, the solutions computed by DIDIC converge to clusterings that are comparable in quality to those computed by the established non-distributed graph clustering library mcl, whose main algorithm uses global knowledge.© 2010 ieee.

关键词： Supercomputers

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