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检索条件"机构=Parallel and Distributed Processing Laboratory School of Computer Engineering"

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A load management system for running HLA-based distributed simulations over the grid

A load management system for running HLA-based distributed s...

引用

International Workshop/Symposium on distributed Simulation and Real-Time Applications (DS-RT)

作者： W. Cai S.J. Turner H. Zhao Parallel and Distributed Processing Laboratory School of Computer Engineering Nanyang Technological University Singapore

Running a large-scale distributed simulation may need a large amount of computing resources at geographically different locations. These resources may be from different organizations. The simulation may run for a long period of time and the availability and amount of computing resources available may change during the course of simulation execution. Therefore, coordinating and managing resources for distributed simulation to complete the simulation efficiently and effectively is a critical issue. This paper describes a load management system for HLA-based distributed simulation. The system is constructed on top of a grid computing environment supported by Globus. The overall structure of the system is presented in the paper and how the system saves and restores a federate is also discussed in detail.

关键词： Load management Computational modeling Resource management distributed computing computer simulation Grid computing Large-scale systems Atherosclerosis Least squares approximation Concurrent computing

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An enhanced smart copying (ESC) method for the reconstruction of missing audio packets

An enhanced smart copying (ESC) method for the reconstructio...

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International Conference on Communications, Circuits and Systems (ICCCAS)

作者： Wei Keng Ng J. Absar S. George C.T. Lau B. Premkumar Parallel & Distributed Processing Lab School of Computer Engineering Nanyang Technological University Singapore STMicroelectronics and University of Pavia Singapore

The paper describes an improved statistical approach for the reconstruction of missing audio packets. We demonstrate that the proposed enhanced smart copying method can successfully reconstruct lost packets with a much reduced computational time (approximately 21 times faster), while giving better quality as compared to the existing scheme. This efficiency is achieved by avoiding the direct inversion of a large matrix and requires no explicit solution for the coefficients of the underlying autoregressive model.

关键词： Microelectronics Asia Streaming media Phase change materials distributed processing Concurrent computing distributed computing Signal reconstruction Signal processing Digital signal processing

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An enhanced smart copying (ESC) method for the reconstruction of missing audio packets 1

An enhanced smart copying (ESC) method for the reconstructio...

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1st International Conference on Communications, Circuits and Systems, ICCCAS 2002

作者： Ng, Wei Keng Absar, J. George, S. Lau, C.T. Premkumar, B. Parallel and Distributed Processing Lab. School of Computer Engineering Nanyang Technological University Nanyang Avenue Singapore639798 Singapore ST Microelectronics Asia Pacific Pte. Ltd. Telectech Park Science Park 2 20 Science Park Road #01-28/30 Singapore117674 Singapore

ISBN: (纸本)0780375475

关键词： Signal reconstruction

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A Java graphical user interface for large-scale scientific computations in distributed systems 4

A Java graphical user interface for large-scale scientific c...

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4th International Conference/Exhibition on High Performance Computing in the Asia-Pacific Region, HPC-Asia 2000

作者： Shen, X. Thiruvathukal, G. Liao, W. Choudhary, A. Singh, A. Center for Parallel and Distributed Computing Department of Electrical and Computer Engineering Northwestern University EvanstonIL60208 United States School of Computing Telecommunications and Information Sciences JHPC Laboratory DePaul University United States

ISBN: (纸本)0769505902

Large-scale scientific applications present great challenges to computational scientists in terms of obtaining high performance and in managing large datasets. These applications (most of which are simulations) may employ multiple techniques and resources in a heterogeneously distributed environment. Effective working in such an environment is crucial for modern large-scale simulations. In this paper, we present an integrated Java graphical user interface (IJ-GUI) that provides a control platform for managing complex programs and their large datasets easily. As far as performance is concerned, we present and evaluate our initial implementation of two optimization schemes: data replication and data prediction. Data replication can take advantage of 'temporal locality' by caching the remote datasets on local disks;data prediction, on the other hand, provides prefetch hints based on the datasets' past activities that are kept in databases. We first introduce the data contiguity concept in such an environment that guides data prediction. The relationship between the two approaches is discussed. © 2000 IEEE.

关键词： Forecasting

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A novel application development environment for large-scale scientific computations 00

A novel application development environment for large-scale ...

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Proceedings of the 14th international conference on Supercomputing

作者： X. Shen W. Liao A. Choudhary G. Memik M. Kandemir S. More G. Thiruvathukal A. Singh Center for Parallel and Distributed Computing Department of Electrical and Computer Engineering Northwestern University Evanston IL Department of Computer Science and Engineering The Pennsylvania State University University Park PA School of Computing Telecommunications and Information Sciences JHPC Laboratory Depaul University

Our results demonstrate that our novel application development environment provides both ease-of-use and high performance for large-scale, I/O-intensive scientific applications.

ISBN: (纸本)9781581132700

Our results demonstrate that our novel application development environment provides both ease-of-use and high performance for large-scale, I/O-intensive scientific applications.

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A parallel algorithm for singular value decomposition as applied to failure tolerant manipulators

A parallel algorithm for singular value decomposition as app...

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International Symposium on parallel processing

作者： T.D. Braun A.A. Maciejewski H.J. Siegel Parallel Processing Laboratory School of Electrical and Computer Engineering Purdue University West Lafayette IN USA

The system of equations that govern kinematically redundant manipulators is commonly solved by finding the singular value decomposition (SVD) of the corresponding Jacobian matrix. This can require considerable amounts of time to compute, thus a parallel SVD algorithm minimizing execution time is sought. The approach employed here lends itself to parallelization by using Givens rotations and information from previous decompositions. The key contributions of this research include the presentation and implementation of a new variation of a parallel SVD algorithm to compute the SVD for a set of post-fault Jacobians. Results from implementation of the algorithm on a MasPar MP-1 and an IBM SP2 are provided. Specific issues considered for each implementation include how data is mapped to the processing elements, the effect that increasing the number of processing elements has on execution time, and the type of parallel architecture used.

关键词： parallel algorithms Singular value decomposition Jacobian matrices Concurrent computing Equations parallel machines Laboratories Matrix decomposition Manipulators Kinematics

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High-performance mixed-machine heterogeneous computing 6

High-performance mixed-machine heterogeneous computing

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6th Euromicro Workshop on parallel and distributed processing, PDP 1998

作者： Maheswaran, Muthucumaru Braun, Tracy D. Siegel, Howard Jay Parallel Processing Laboratory School of Electrical and Computer Engineering Purdue University West LafayetteIN47907-1285 United States

ISBN: (纸本)0818683325

The focus of this invited keynote paper (to be presented by H. J. Siegel) is mixed-machine heterogeneous computing, where a suite of different kinds of high-performance machines are interconnected by high-speed links. Such a system can be orchestrated to perform an application whose subtasks have diverse execution requirements. Subtasks are assigned to and executed on the machines that will result an a minimal overall execution time for the task, considering factors including anter-machine communication overhead. A conceptual model of the automatic decomposition of tasks and assignment of subtasks is presented. Examples of static and dynamic approaches to the matching and scheduling of subtasks are summarized. Some open research problems are dascussed. © 1998 IEEE

关键词： computers

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A dynamic matching and scheduling algorithm for heterogeneous computing systems

A dynamic matching and scheduling algorithm for heterogeneou...

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Heterogeneous Computing Workshop

作者： M. Maheswaran H.J. Siegel Parallel Processing Laboratory School of Electrical and Computer Engineering Purdue University West Lafayette USA

A heterogeneous computing system provides a variety of different machines, orchestrated to perform an application whose subtasks have diverse execution requirements. The subtasks must be assigned to machines (matching) and ordered for execution (scheduling) such that the overall application execution time is minimized. A new dynamic mapping (matching and scheduling) heuristic called the hybrid remapper is presented here. The hybrid remapper is based on a centralized policy and improves a statically, obtained initial matching and scheduling by remapping to reduce the overall execution time. The remapping is non-preemptive and the execution of the hybrid remapper can be overlapped with the execution of the subtasks. During application execution, the hybrid remapper uses run-time values for the subtask completion times and machine availability times whenever possible. Therefore, the hybrid remapper bases its decisions on a mixture of run-time and expected values. The potential of the hybrid remapper to improve the performance of initial static mappings is demonstrated using simulation studies.

关键词： Scheduling algorithm Processor scheduling Runtime Dynamic scheduling Availability

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High-performance mixed-machine heterogeneous computing

High-performance mixed-machine heterogeneous computing

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Euromicro Workshop on parallel and distributed processing

作者： M. Maheswaran T.D. Braun H.J. Siegel Parallel Processing Laboratory School of Electrical and Computer Engineering Purdue University West Lafayette IN USA Purdue University System West Lafayette IN US

The focus of this invited keynote paper (to be presented by H.J. Siegel) is mixed-machine heterogeneous computing, where a suite of different kinds of high-performance machines are interconnected by high-speed links. Such a system can be orchestrated to perform an application whose subtasks have diverse execution requirements. Subtasks are assigned to and executed on the machines that will result in a minimal overall execution time for the task, considering factors including inter-machine communication overhead. A conceptual model of the automatic decomposition of tasks and assignment of subtasks is presented. Examples of static and dynamic approaches to the matching and scheduling of subtasks are summarized. Some open research problems are discussed.

关键词： Concurrent computing Processor scheduling Dynamic scheduling Application software computer architecture parallel processing Laboratories Indium tin oxide Subcontracting Heuristic algorithms

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Benchmarking the task graph scheduling algorithms

Benchmarking the task graph scheduling algorithms

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International Symposium on parallel processing

作者： Y.-K. Kwok I. Ahmad Parallel Processing Laboratory School of Electrical and Computer Engineering Purdue University West Lafayette IN USA Department of Computer Science Hong Kong University of Science and Technology Hong Kong China

The problem of scheduling a weighted directed acyclic graph (DAG) to a set of homogeneous processors to minimize the completion time has been extensively studied. The NP-completeness of the problem has instigated researchers to propose a myriad of heuristic algorithms. While these algorithms are individually reported to be efficient, it is not clear how effective they are and how well they compare against each other. A comprehensive performance evaluation and comparison of these algorithms entails addressing a number of difficult issues. One of the issues is that a large number of scheduling algorithms are based upon radically different assumptions, making their comparison on a unified basis a rather intricate task. Another issue is that there is no standard set of benchmarks that can be used to evaluate and compare these algorithms. Furthermore, most algorithms are evaluated using small problem sizes, and it is not clear how their performance scales with the problem size. The authors first provide a taxonomy for classifying various algorithms into different categories according to their assumptions and functionalities. They then propose a set of benchmarks which are of diverse structures without being biased towards a particular scheduling technique and still allow variations in important parameters. They have evaluated 15 scheduling algorithms, and compared them using the proposed benchmarks. Based upon the design philosophies and principles behind these algorithms, they interpret the results and discuss why some algorithms perform better than the others.

关键词： Scheduling algorithm Processor scheduling parallel processing Concurrent computing Heuristic algorithms Laboratories computer science Taxonomy Algorithm design and analysis Scalability

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