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A Self-Stabilization Process for Small-World Networks

A Self-Stabilization Process for Small-World Networks

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26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive computing

作者： Kniesburges, Sebastian Koutsopoulos, Andreas Scheideler, Christian Univ Gesamthsch Paderborn Dept Comp Sci D-4790 Paderborn Germany

ISBN: (纸本)9780769546759

Small-world networks have received significant attention because of their potential as models for the interaction networks of complex systems. Specifically, neither random networks nor regular lattices seem to be an adequate framework within which to study real-world complex systems such as chemical-reaction networks, neural networks, food webs, social networks, scientific-collaboration networks, and computer networks. Small-world networks provide some desired properties like an expected polylogarithmic distance between two processes in the network, which allows routing in polylogarithmic hops by simple greedy routing, and robustness against attacks or failures. By these properties, small-world networks are possible solutions for large overlay networks comparable to structured overlay networks like CAN, Pastry, Chord, which also provide polylogarithmic routing, but due to their uniform structure, structured overlay networks are more vulnerable to attacks or failures. In this paper we bring together a randomized process converging to a small-world network and a self-stabilization process so that a small-world network is formed out of any weakly connected initial state. To the best of our knowledge this is the first distributed self-stabilization process for building a small-world network.

关键词： small-world network self-stabilization distributed algorithms

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Analysis of Data Reliability Tradeoffs in Hybrid distributed Storage Systems

Analysis of Data Reliability Tradeoffs in Hybrid Distributed...

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26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive computing

作者： Tang, Bing Fedak, Gilles Univ Lyon INRIA LIP F-69364 Lyon 07 France

ISBN: (纸本)9780769546766

This paper surveys previous distributed storage systems and related data redundancy and fault-tolerance schemes which are introduced to overcome the impact of host churn on data reliability. Furthermore, a hybrid storage system model is proposed which offers a reliable data storage service by integrating idle storage contributed by volatile peer nodes and stable and durable storage utilities. In order to ensure high availability and durability for this hybrid storage system, we explore four reliability improvement strategies, including File Replica Strategy, File Encoding Strategy, Replica Repair Strategy, and Stable-Volatile Strategy, as well as the combination of these four strategies. Extensive simulations based on real traces are performed, in which data availability, data durability, and storage overhead are evaluated. Simulation results show that compared with previous peer-to-peer storage systems, the proposed hybrid storage system could achieve a higher availability and durability with less storage consumption, due to proposed new strategies. Finally, taking into account storage and traffic cost, the tradeoffs between storage efficiency and reliability are discussed.

关键词： Peer-to-Peer Hybrid Storage System Reliability Tradeoff Availability Durability

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Opportunistic Data-driven Execution of parallel Programs for Efficient I/O Services

Opportunistic Data-driven Execution of Parallel Programs for...

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26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive computing

作者： Zhang, Xuechen Davis, Kei Jiang, Song Wayne State Univ ECE Dept Detroit MI 48202 USA Los Alamos Natl Lab CCS Div Los Alamos NM 87545 USA

ISBN: (纸本)9780769546759

A parallel system relies on both process scheduling and I/O scheduling for efficient use of resources, and a program's performance hinges on the resource on which it is bottlenecked. Existing process schedulers and I/O schedulers are independent. However, when the bottleneck is I/O, there is an opportunity to alleviate it via cooperation between the I/O and process schedulers: the service efficiency of I/O requests can be highly dependent on their issuance order, which in turn is heavily influenced by process scheduling. We propose a data-driven program execution mode in which process scheduling and request issuance are coordinated to facilitate effective I/O scheduling for high disk efficiency. Our implementation, DualPar, uses process suspension and resumption, as well as pre-execution and prefetching techniques, to provide a pool of pre-sorted requests to the I/O scheduler. This data-driven execution mode is enabled when I/O is detected to be the bottleneck, otherwise the program runs in the normal computation-driven mode. DualPar is implemented in the MPICH2 MPI-IO library for MPI programs to coordinate I/O service and process execution. Our experiments on a 120-node cluster using the PVFS2 file system show that DualPar can increase system I/O throughput by 31% on average, compared to existing MPI-IO with or without using collective I/O.

关键词： Process Scheduling I/O Request Scheduling Prefetching

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distributed computation and large-scale visualization in heterogeneous compute environments

Distributed computation and large-scale visualization in het...

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2012 11th international symposium on parallel and distributed computing, ISPDC 2012

作者： Panagiotidis, Alexandros Kauker, Daniel Sadlo, Filip Ertl, Thomas Visualization and Interactive Systems Group University of Stuttgart Stuttgart Germany

ISBN: (纸本)9780769548050

High performance computing still typically disregards heterogeneous environments and focuses on homogeneous clusters. While providing advantages and easing development, this fails to address the recent change toward heterogeneous computing infrastructure. With DIANA we presented an abstraction layer for unified access to local compute hardware including different hardware APIs. In this paper we extend DIANA, enabling transparent access to remote hardware. In this context, we demonstrate how to use DIANA for distributed computation and large-scale visualization of the finite-time Lyapunov exponent field in heterogeneous environments. © 2012 IEEE.

关键词： Visualization

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A Simulation Study on Urban Water Threat Detection in Modern Cyberinfrastructures

A Simulation Study on Urban Water Threat Detection in Modern...

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26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive computing

作者： Wang, Lizhe Chen, Dan Deng, Ze Ranjan, Rajiv Chinese Acad Sci Ctr Earth Observat & Digital Earth Beijing 100864 Peoples R China China Univ Geosci Sch Comp Sci Wuhan Peoples R China CSIRO ICT Ctr Marsfield NSW Australia

ISBN: (纸本)9780769546766

The computation of Contaminant Source Characterization (CSC) is a critical research issue in Water Distribution System (WDS) management. We use a simulation framework to identify optimized locations of sensors that lead to fast detection of contamination sources. The optimization engine is based on a Genetic Algorithm (GA) that interprets trial solutions as individuals. During the optimization process many thousands of these solutions are generated. For a large WDS, the calculation of these solutions are non-trivial and time consuming. Hence, it is a compute intensive application that requires significant compute resources. Furthermore, we strive to generate solutions quickly in order to respond to the urgency of a response. To carry out the calculations we require user-level middleware that can be supporting the workflow of the application and manages the resource assignment in an efficient and fault tolerant fashion. To do so we have prototyped the middleware framework that provides a convenient command line and portal layer of steering applications on Grids. Internally, we utilize a sophisticated workflow engine that provides the ability to access elementary fault tolerant mechanisms for job scheduling. This includes the management of job replicas and the reaction on late return of results. We report the test results of CSC problem solving on a real Grid test bed - the TeraGrid test bed. In addition, we contrast this system architecture with a Hadoop-based implementation that automatically includes fault tolerance. The later activity has been conducted on FutureGrid.

关键词： Cloud computing Grid computing Hadoop parallel Simulation

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Improving parallel IO Performance of Cell-based AMR Cosmology Applications

Improving Parallel IO Performance of Cell-based AMR Cosmolog...

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26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive computing

作者： Yu, Yongen Rudd, Douglas H. Lan, Zhiling Gnedin, Nickolay Y. Kravtsov, Andrey Wu, Jingjin IIT Dept Comp Sci Chicago IL 60616 USA Yale Univ Yale Ctr Astron & Astrophys New Haven CT 06520 USA Univ Chicago Dept Astron & Astrophys Chicago IL 60637 USA Fermilab Natl Accelerator Lab Theor Astrophys Grp Batavia IL USA

ISBN: (纸本)9780769546759

To effectively model various regions with different resolutions, adaptive mesh refinement (AMR) is commonly used in cosmology simulations. There are two well-known numerical approaches towards the implementation of AMR-based cosmology simulations: block-based AMR and cell-based AMR. While many studies have been conducted to improve performance and scalability of block-structured AMR applications, little work has been done for cell-based simulations. In this study, we present a parallel IO design for cell-based AMR cosmology applications, in particular, the ART(Adaptive Refinement Tree) code. First, we design a new data format that incorporates a space filling curve to map between spatial and on-disk locations. This indexing not only enables concurrent IO accesses from multiple application processes, but also allows users to extract local regions without significant additional memory, CPU or disk space overheads. Second, we develop a flexible N-M mapping mechanism to harvest the benefits of N-N and N-1 mappings where N is number of application processes and M is a user-tunable parameter for number of files. It not only overcomes the limited bandwidth issue of an N-1 mapping by allowing the creation of multiple files, but also enables users to efficiently restart the application at a variety of computing scales. Third, we develop a user-level library to transparently and automatically aggregate small IO accesses per process to accelerate IO performance. We evaluate this new parallel IO design by means of real cosmology simulations on production HPC system at TACC. Our preliminary results indicate that it can not only provide the functionality required by scientists (e.g., effective extraction of local regions and flexible process-tofile mapping), but also significantly improve IO performance.

关键词： parallel I/O adaptive mesh refinement data layout high performance computing cosmology simulations

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Consistency-aware Partitioning Algorithm in Multi-server distributed Virtual Environments

Consistency-aware Partitioning Algorithm in Multi-server Dis...

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26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive computing

作者： Li, Yusen Cai, Wentong Nanyang Technol Univ Parallel & Distributed Comp Ctr Singapore 639798 Singapore

ISBN: (纸本)9780769546759

In DVEs, the primary task is to maintain a consistent view of the virtual world among all users. Multi-server architecture has been shown to have good scalability to support a large population of users in DVEs. One of the key issues in the design of an efficient and scalable Multi-server distributed Virtual Environment (MSDVE) is the partitioning, which concerns with efficiently distributing the workload generated in the virtual environment among multiple servers in the system. Most of the existing work on the partitioning issue in MSDVE aims to either balance workload among servers, reduce inter-server communication, and/or improve the interactivity of DVE. In this paper, we study the partitioning issue from a new perspective and aim to reduce the time-space inconsistency of a DVE. Time-space inconsistency is a consistency metric, which has been proven to be an effective performance measure of DVEs. Using the time-space inconsistency metric, we formally formulate our partitioning problem as a mix integer programming problem and propose a solution based on Alternating Optimization (AO) technique. An iterative partitioning algorithm is also developed accordingly. The algorithm gives a partition as well as the corresponding update schedule to minimize the total time-space inconsistency. Different from most of the existing work, the resulted partition is avatar-based rather than zone/region-based. To evaluate the performance of the proposed partitioning algorithm, extensive experiments were conducted and results are reported in the paper.

关键词： distributed virtual environment MSDVEs time-space consistency partitioning Alternating Optimization

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ShyLU: A Hybrid-Hybrid Solver for Multicore Platforms

ShyLU: A Hybrid-Hybrid Solver for Multicore Platforms

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26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive computing

作者： Rajamanickam, Sivasankaran Boman, Erik G. Heroux, Michael A. Sandia Natl Labs Livermore CA 94550 USA

ISBN: (纸本)9780769546759

With the ubiquity of multicore processors, it is crucial that solvers adapt to the hierarchical structure of modern architectures. We present ShyLU, a "hybrid-hybrid" solver for general sparse linear systems that is hybrid in two ways: First, it combines direct and iterative methods. The iterative part is based on approximate Schur complements where we compute the approximate Schur complement using a value-based dropping strategy or structure-based probing strategy. Second, the solver uses two levels of parallelism via hybrid programming (MPI+threads). ShyLU is useful both in shared-memory environments and on large parallel computers with distributed memory. In the latter case, it should be used as a subdomain solver. We argue that with the increasing complexity of compute nodes, it is important to exploit multiple levels of parallelism even within a single compute node. We show the robustness of ShyLU against other algebraic preconditioners. ShyLU scales well up to 384 cores for a given problem size. We also study the MPI-only performance of ShyLU against a hybrid implementation and conclude that on present multicore nodes MPI-only implementation is better. However, for future multicore machines (96 or more cores) hybrid/hierarchical algorithms and implementations are important for sustained performance.

关键词： Solvers Multi-core processors modern architectures parallelism distributed memory HYBRID hierarchical structure instruction-level parallelism Synclitism

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Scalable Critical-Path Based Performance Analysis

Scalable Critical-Path Based Performance Analysis

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26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive computing

作者： Boehme, David Wolf, Felix de Supinski, Bronis R. Schulz, Martin Geimer, Markus German Res Sch Simulat Sci D-52062 Aachen Germany Lawrence Livermore Natl Lab Livermore CA USA Julich Supercomp Ctr D-52425 Julich Germany

ISBN: (纸本)9780769546759

The critical path, which describes the longest execution sequence without wait states in a parallel program, identifies the activities that determine the overall program runtime. Combining knowledge of the critical path with traditional parallel profiles, we have defined a set of compact performance indicators that help answer a variety of important performance-analysis questions, such as identifying load imbalance, quantifying the impact of imbalance on runtime, and characterizing resource consumption. By replaying event traces in parallel, we can calculate these performance indicators in a highly scalable way, making them a suitable analysis instrument for massively parallel programs with thousands of processes. Case studies with real-world parallel applications confirm that-in comparison to traditional profiles-our indicators provide enhanced insight into program behavior, especially when evaluating partitioning schemes of MPMD programs.

关键词： performance indicators parallel programming Runtime Program Behavior Scalability Resource utilization Critical Pathways critical path analysis parallel Lines unbalanced load

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A distributed Solver for Dense Linear Feasibility Systems

A Distributed Solver for Dense Linear Feasibility Systems

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14th international symposium on Symbolic and Numeric Algorithms for Scientific computing (SYNASC)

作者： Sucila, Andrei Cimpoesu, Mihai Alexandru Ioan Cuza Univ Fac Comp Sci Iasi Romania

ISBN: (纸本)9780769549347;9781467350266

The aim of this paper is to present a new hybrid solver for linear feasibility systems that uses a block-parallel scheme combined with a new variable weight projection operator which takes into account the distances to the semispaces onto which it projects. The solver can tackle very large, dense, systems. The results of our study show that a specialized variant of the solver is more efficient at solving a certain class of dense systems in terms of resources than other variants. Furthermore, we will also show results that suggest that the distribution scheme does not greatly affect the number of required iterations for a solution to be reached.

关键词： iterative methods mathematical operators parallel algorithms

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