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A software-based MPEG-4 video encoder using parallel processing

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 1998年第7期8卷 909-920页

作者： He, Y Ahmad, I Liou, ML Hong Kong Univ Sci & Technol Dept Elect & Elect Engn Kowloon Hong Kong Hong Kong Univ Sci & Technol Dept Comp Sci Kowloon Hong Kong

In this paper, we describe a software-based MPEG-4 video encoder which is implemented using parallel processing on a cluster of workstations collectively working as a virtual machine. The contributions of our work are as follows. First, a hierarchical Petri-nets-based modeling methodology is proposed to capture the spatiotemporal relationships among multiple objects at different levels of an MPEG-4 video sequence, Second, a scheduling algorithm is proposed to assign video objects to workstations for encoding in parallel, The algorithm determines the execution order of video objects, ensures that the synchronization requirements among them are enforced and that presentation deadlines are met, Third, a dynamic partitioning scheme is proposed which divides an object among multiple workstations to extract additional parallelism, The scheme achieves load balancing among the workstations with a low overhead, The striking feature of our encoder is that it adjusts the allocation and partitioning of objects automatically according to the dynamic variations in the video object behavior. We have made various additional software optimizations to further speed up the computation. The performance of the encoder can scale according to the number of workstations used. With 20 workstations, the encoder yields an encoding rate higher than real time, allowing the encoding of multiple sequences simultaneously.

关键词： data partitioning dynamic scheduling load balancing MPEG-4 parallel and distributed processing Petri nets video encoder

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parallel processing applied to the planning of hydrothermal systems

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IEEE TRANSACTIONS ON parallel AND distributed SYSTEMS 2003年第8期14卷 721-729页

作者： da Silva, EL Finardi, EC Univ Fed Santa Catarina Lab Planejamento Sistemas Energia Eletr Labplan Programa Posgrad Engn EletrPPGEELCtr Technol BR-88040900 Florianopolis SC Brazil

The objective of the long-term operating planning problem is to determine the optimum strategy for the generation of electricity, aiming toward the minimization of total operating cost over the planning period. In a competitive electricity market, with the participation of a significant number of hydroplants, such as in Brazil, precision modeling for operating planning is required so that a better use of hydraulic resources can be obtained. Therefore, in this paper, we present a long-term operating planning model based on an individual power plant representation. In order to support the high computational burden, a suitable parallel processing algorithm is proposed.

关键词： hydrothermal systems stochastic optimization control problems parallel and distributed processing

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Adaptive message routing in a class of fault-tolerant multistage interconnection networks

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COMPUTERS & ELECTRICAL ENGINEERING 1997年第4期23卷 239-247页

作者： Zhou, YQ Min, YH CHINESE ACAD SCI INST COMP TECHNOL BEIJING 100080 PEOPLES R CHINA

Multistage interconnection networks (MINs) are often used to provide interconnections in multiprocessor systems. A unique path MIN usually has lower hardware complexity and simple control algorithm, but it lacks fault-tolerance. This paper proposes a class of multipath MINs,which are obtained by adding auxiliary links at the final stage in quad tree networks so that they can provide more paths between each source-destination pair, and presents their routing algorithm which is both destination tag based and adaptive. Starting with the routing: tag for the minimum path between a given source-destination pair, the routing algorithm uses a set of rules to select switches and modify routing tag. In addition to trying the auxiliary link when both of the output links are unavailable, the second output link is tried before the auxiliary link when the first output link is unavailable. This feature distinguishes the proposed routing algorithm from the one for quad tree networks and makes better use of all the possible paths between the given source-destination pair. At the end of this paper, an index of performance called capacity is introduced to compare different kinds of MINs. Comparison shows that the proposed MINs have better capacity than quad tree networks. (C) 1997 Elsevier Science Ltd.

关键词： communication fault-tolerance multistage interconnection networks parallel and distributed processing

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parallel molecular dynamics simulation: implementation of PVM for a lipid membrane

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COMPUTER PHYSICS COMMUNICATIONS 1999年第2-3期116卷 295-310页

作者： Fang, ZW Haymet, ADJ Shinoda, W Okazaki, S Univ Houston Dept Chem Houston TX 77204 USA Univ Sydney Sch Chem F11 Sydney NSW 2006 Australia Tokyo Inst Technol Dept Elect Chem Midori Ku Yokohama Kanagawa 226 Japan

This paper describes a parallel algorithm for Molecular Dynamics simulation of a lipid membrane using the isothermal-isobaric ensemble. A message-passing paradigm is adopted for interprocessor communications using PVM3 (parallel Virtual Machine). A data decomposition technique is employed for the parallelization of the calculation of intermolecular forces. The algorithm has been tested both on distributed memory architecture (DEC Alpha 500 workstation dusters) and shared memory architecture (SGI Powerchallenge with 20 R10000 processors) for a dipalmitoylphosphatidylcholine (DPPC) lipid bilayer consisting of 32 DPPC molecules and 928 water molecules. For each architecture, we measure the execution time with average work load, and the optimal number of processors for the current simulation. Some dynamical quantities are presented for a 2 ns simulation obtained with 5 processors on DEC Alpha 500 workstations. Our results show that the code is extremely efficient on 5-8 processors, and a useful addition to other major computational resources. (C) 1999 Published by Elsevier Science B.V.

关键词： lipid simulation parallel and distributed processing PVM

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distributed Multi-Feature Recognition Scheme for Greyscale Images

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NEURAL processing LETTERS 2011年第1期33卷 45-59页

作者： Amin, Anang Hudaya Muhamad Khan, Asad I. Univ Teknol PETRONAS Comp & Informat Sci Dept Tronoh 31750 Perak Darul Rid Malaysia Monash Univ Clayton Sch Informat Technol Clayton Vic 3168 Australia

Contemporary image recognition schemes either rely on single-feature recognition or focus on solving multi-feature recognition using complex computational approaches. Furthermore these approaches tend to be of tightly-coupled nature, thus not readily deployable within computational networks. distributed Hierarchical Graph Neuron (DHGN) is a distributed single-cycle learning pattern recognition algorithm that can scale from coarse-grained to fine-grained networks and it has comparable accuracy to contemporary image recognition schemes. In this paper, we present an implementation of DHGN that works for multi-feature recognition of images. Our scheme is able to disseminate recognition of each feature within an image to a separate computational subnetwork. Thereby allowing a number of features being analysed simultaneously using a uniform recognition process. We have conducted tests on a collection of greyscale facial images. The results show that our approach produces high recognition accuracy through a simple distributed process. Furthermore, our approach implements single-cycle learning known as collaborative-comparison learning where new patterns are continuously stored using collaborative approach without affecting previously stored patterns. Our proposed scheme demonstrates higher classification accuracy in comparison with Back-Propagation Neural Network for multi-class images.

关键词： Multi-feature recognition parallel and distributed processing Neural networks distributed hierarchical graph neuron

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ORGANIZATION SELF-DESIGN OF distributed PRODUCTION SYSTEMS

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 1992年第2期4卷 123-134页

作者： ISHIDA, T GASSER, L YOKOO, M UNIV SO CALIF DEPT COMP SCI LOS ANGELES CA 90089 USA

Organization has emerged as a key concept for structuring the activities of collections of problem-solvers. Organization self-design (OSD) has been studied as an adaptive approach to long term, strategic work-allocation and load-balancing. In this paper, we introduce two new reorganization primitives, composition and decomposition. They change the population of agents and the distribution of knowledge in an organization. To create these primitives, we formalize organizational knowledge, which represents knowledge of potential and necessary interactions among agents in an organization. We develop computational OSD techniques for agents with architectures based on production systems to take advantage of the well-understood body of theory and practice. We first extend parallel production systems, where global control exists, into distributed production systems, where problems are solved by a society of agents using distributed control. We then introduce OSD into distributed production systems to provide adaptive work allocation. Simulation results demonstrate the, effectiveness of our approach in adapting to changing environmental demands. In addition to introducing advanced techniques for flexible OSD, our approach impacts production system design, and improves our ability to build production systems that can adapt to changing real-time constraints.

关键词： ADAPTIVE PROBLEM SOLVING ORGANIZATION SELF-DESIGN parallel and distributed processing PRODUCTION SYSTEM REAL-TIME PROBLEM SOLVING

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SCALA: A performance system for scalable computing

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INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS 2002年第4期16卷 357-370页

作者： Sun, XH Fahringer, T Pantano, M IIT Dept Comp Sci Chicago IL 60616 USA Univ Vienna Inst Software Technol & Parallel Syst A-1090 Vienna Austria

Lack of effective performance-evaluation environments is a major barrier to the broader use of high performance computing. Conventional performance environments are based on profiling and event instrumentation. It becomes problematic as parallel systems scale to hundreds of nodes and beyond. A framework of developing an integrated performance modeling and prediction system, SCALability Analyzer (SCALA), is presented in this study. In contrast to existing performance tools, the program performance model generated by SCALA is based on scalability analysis. SCALA assumes the availability of modern compiler technology, adopts statistical and symbolic methodologies, and has the support of browser interface. These technologies, together with a new approach of scalability analysis, enable SCALA to provide the user with a more intuitive level of performance analysis for scalable computing. A prototype SCALA system has been implemented. Initial experimental results show that SCALA is unique in its ability of revealing the scaling properties of a computing system.

关键词： software system performance evaluation parallel and distributed processing scalability analysis symbolic analysis statistical analysis

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TeraGrid GIScience Gateway: Bridging cyberinfrastructure and GIScience

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INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE 2009年第5期23卷 631-656页

作者： Wang, Shaowen Liu, Yan Univ Illinois Dept Geog Urbana IL 61801 USA Univ Illinois Natl Ctr Supercomp Applicat Urbana IL 61801 USA

Cyberinfrastructure (CI) represents the integrated information and communication technologies for distributed information processing and coordinated knowledge discovery, and is promising to revolutionize how science and engineering are conducted in the twenty-first century. The value of bridging CI and GIScience is significant to advance CI and benefit GIScience research and education, particularly in distributed geographic information processing (DGIP). This article presents a holistic framework that bridges CI and GIScience by integrating CI capabilities to empower GIScience research and education and establish generic DGIP services supported by CI. The framework, the TeraGrid GIScience Gateway, is based on a CI science gateway approach developed on the National Science Foundation (NSF) TeraGrid - a key element of US and world CI. This gateway develops a unifying service-oriented framework with respect to its architecture, design, and implementation as well as its integration with the TeraGrid. The functions of the gateway focus on enabling parallel and distributed processing for geographical analysis, managing the complexity of TeraGrid software environment, and establishing a Web-based GIS for the GIScience community to gain shared and collaborative access to TeraGrid-based geospatial processing services. The gateway implementation uses Web 2.0 technologies to create a highly configurable and interactive multiuser environment. Two case studies, Bayesian geostatistical modeling and a spatial statistic [image omitted] for detecting local clustering, are used to demonstrate the gateway functions and user environment. The service transformation for these analyses is applied to create a shared, decentralized, and collaborative geographical analysis environment in which GIScience community users can contribute new analysis services and reuse existing gateway services.

关键词： Cyberinfrastructure Geographical analysis parallel and distributed processing Service-oriented architecture Web 2.0 Web-based GIS

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Effectively Handling New Relationship Formations in Closeness Centrality Analysis of Social Networks using Anytime Anywhere Methodology 6

Effectively Handling New Relationship Formations in Closenes...

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2016 IEEE International Conferences on BDCloud/SocialCom/SustainCom 2016

作者： Santos, Eunice E. Korah, John Murugappan, Vairavan Subramanian, Suresh IIT Dept Comp Sci Chicago IL 60616 USA

ISBN: (纸本)9781509039364

The flood of real time social data, generated by various social media applications and sensors, is enabling researchers to gain critical insights into important social modeling and analysis problems such as the evolution of social relationships and analysis of emergent social processes. However, current computational tools have to address the grand challenge of analyzing large and dynamic social networks within strict time constraints before the available social data can be effectively utilized. The computational issues are further exacerbated by the network size, which can range in the millions of nodes, and by the need for analytical tools to work with various computational architectures. Existing methodologies primarily deal with dynamic relationships in social networks by simply re-computing the results, and relying on massive parallel and distributed processing resources to maintain time constraints. In previous work, we introduced an overarching parallel/distributed algorithm design framework called the anytime anywhere framework, which leverages the inherent iterative property of graph algorithms to generate partial results, whose quality increase with the processing time, and which efficiently incorporates network changes. In this paper, we focus on closeness centrality algorithm design for dynamic social networks where new relationships are formed due to edge additions. Using both theoretical analysis and empirical results, we will demonstrate how this algorithm efficiently reuses the partial results and reduces the need for re-computations.

关键词： social network analysis parallel and distributed processing centrality analysis dynamic graphs anytime algorithms

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Efficient Anytime Anywhere Algorithms for Vertex Additions in Large and Dynamic Graphs 31

Efficient Anytime Anywhere Algorithms for Vertex Additions i...

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31st IEEE International parallel and distributed processing Symposium Workshops (IPDPS)

作者： Santos, Eunice E. Korah, John Murugappan, Vairavan Subramanian, Suresh IIT Dept Comp Sci Chicago IL 60616 USA

ISBN: (纸本)9780769561493

Over the past decade, there has been a dramatic increase in the availability of large and dynamic social network datasets. Conducting social network analysis (SNA) on these networks is critical for understanding underlying social phenomena. However, continuously evolving graph structures require massive recomputations and conducting SNA is infeasible if the computations have to be restarted for every change. Many recent works have proposed large-scale graph processing systems and frameworks, but less attention has been given to scalable SNA algorithm designs that can efficiently adapt to dynamic graph changes. Moreover, continuously adapting to dynamic graph changes such as node/vertex/actor additions/deletions in a parallel/distributed computational environment can skew the initial graph partitions, leading to load imbalance issues and performance degradation. Previous approaches that focus on computing SNA measures on dynamic graphs either ignore this critical load-balancing aspect or focus only on measures that are straightforward and inherently adjustable to changes in the graph topology. In this work, we have designed an anytime anywhere closeness centrality algorithm that can efficiently incorporate vertex additions while avoiding massive recomputations, by leveraging a generic framework for designing parallel/distributed algorithms called anytime anywhere. Furthermore, we have also performed an analysis of the effectiveness of various processor assignment strategies to mitigate the load imbalances caused by dynamic graph changes.

关键词： social network analysis parallel and distributed processing centrality analysis dynamic graphs anytime anywhere algorithms dynamic vertex addition

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