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1999 ACM/IEEE Conference on Supercomputing, SC 1999

作者： Mahinthakumar, G. Hoffman, Forrest M. Hargrove, William W. Karonis, Nicholas T. Oak Ridge National Laboratory Center for Computational Sciences P. O. Box 2008 Oak RidgeTN37831-6203 United States University of Tennessee Energy Environment Resources Center Systems Development Institute 10521 Research Drive KnoxvilleTN37932 United States High Performance Computing Laboratory Department of Computer Science Northern Illinois University DekalbIL60115 United States

ISBN: (纸本)1581130910

The authors present a metacomputing application of multivariate, nonhierarchical statistical clustering to geographic environmental data from the 48 conterminous United States in order to produce maps of regions of ecological similarity, called ecoregions. These maps represent finer scale regionalizations than do those generated by the traditional technique: an expert with a marker pen. Several variables (e.g., temperature, organic matter, rainfall etc.) thought to affect the growth of vegetation are clustered at resolutions as fine as one square kilometer (1 km2). These data can represent over 7.8 million map cells in an n-dimensional (n = 9 to 25) data space. A parallel version of the iterative statistical clustering algorithm is developed by the authors using the MPI (Message Passing Interface) message passing routines. The parallel algorithm uses a classical, self-scheduling, single-program, multiple data (SPMD) organization;performs dynamic load balancing for reasonable performance in heterogeneous metacomputing environments;and provides fault tolerance by saving intermediate results for easy restarts in case of hardware failure. The parallel algorithm was tested on various geographically distributed heterogeneous metacomputing configurations involving an IBM SP3™, an IBM SP2™, and two SGI Origin 2000™'s. The tests were performed with minimal code modification, and were made possible by Globus™ (a metacomputing software toolkit) and the Globus-enabled version of MPI (MPICH-G). Our performance tests indicate that while the algorithm works reasonably well under the metacomputing environment for a moderate number of processors, the communication overhead can become prohibitive for large processor configurations. © 1999 IEEE.

关键词： Message passing

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Utilization of matrix structure to generate optimized code from MATLAB programs

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International Journal of Parallel Programming 1999年第2期27卷 73-96页

作者： Marsolf, Bret A. Gallivan, Kyle A. Wijshoff, Harry A. G. DEMACO Inc. Champaign IL United States Compl. Sci. and Engineering Program Florida State University Tallahassee FL United States High Performance Computing Division Department of Computer Science Leiden University Leiden Netherlands

The FALCON development environment was designed around three basic data representations: scalars, vectors, and dense matrices. Utilizing the FALCON interactive restructuring system, the environment has been enhanced to allow the identification of structures within sparse matrices, such as diagonal matrices or symmetric matrices, and the use of this information for improving performance of the generated code. In addition, the environment supports the modification of the representation of the data. Such modifications have been shown to provide significant performance improvements.

关键词： computer programming

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Structured spatial domain image and data comparison metrics

Structured spatial domain image and data comparison metrics

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IEEE Conference on Visualization

作者： N. Sahasrabudhe J.E. West R. Machiraju M. Janus NSF Engineering Research Center Mississippi State University USA DoD High Performance Computing Center Information Technology Laboratory USAE Waterways Experiment Station USA Department of Computer Science NSF Engineering Research Center Mississippi State University USA Department of AeroSpace Engineering NSF Engineering Research Center Mississippi State University USA

ISBN: (纸本)078035897X

Often, images or datasets have to be compared to facilitate choices of visualization and simulation parameters respectively. Common comparison techniques include side-by-side viewing and juxtaposition, in order to facilitate visual verification of verisimilitude. We propose quantitative techniques which accentuate differences in images and datasets. The comparison is enabled through a collection of partial metrics which, essentially, measure the lack of correlation between the datasets or images being compared. That is, they attempt to expose and measure the extent of the inherent structures in the difference between images or datasets. Besides yielding numerical attributes, the metrics also produce images which can visually highlight differences. Our metrics are simple to compute and operate in the spatial domain. We demonstrate the effectiveness of our metrics through examples for comparing images and datasets.

关键词： Image generation Rendering (computer graphics) Data visualization high performance computing Information technology Laboratories computer science Aerospace engineering Data engineering Computational modeling

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Structured spatial domain image and data comparison metrics 99

Structured spatial domain image and data comparison metrics

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Proceedings of the conference on Visualization '99: celebrating ten years

作者： Nivedita Sahasrabudhe John E. West Raghu Machiraju Mark Janus NSF Engineering Research Center Mississippi State University DoD High Performance Computing Center Information Technology Laboratory USAE Waterways Experiment Station and NSF Engineering Research Center Mississippi State University Department of Computer Science NSF Engineering Research Center Mississippi State University Department of Aerospace Engineering NSF Engineering Research Center Mississippi State University

ISBN: (纸本)9780780358973

Often, images or datasets have to be compared, to facilitate choices of visualization and simulation parameters respectively. Common comparison techniques include side-by-side viewing and juxtaposition, in order to facilitate visual verification of verisimilitude. In this paper, we propose quantitative techniques which accentuate differences in images and datasets. The comparison is enabled through a collection of partial metrics which, essentially, measure the lack of correlation between the datasets or images being compared. That is, they attempt to expose and measure the extent of the inherent structures in the difference between images or datasets. Besides yielding numerical attributes, the metrics also produce images, which can visually highlight differences. Our metrics are simple to compute and operate in the spatial domain. We demonstrate the effectiveness of our metrics through examples for comparing images and datasets.

关键词： correlation measure rendering metrics steering

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Multivariate Geographic Clustering in A Metacomputing Environment Using Globus

Multivariate Geographic Clustering in A Metacomputing Enviro...

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Supercomputing Conference

作者： G. Mahinthakumar F.M. Hoffman W.W. Hargrove N.T. Karonis Oak Ridge National Laboratory Center for Computational Sciences Oak Ridge TN USA Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge TN USA Energy Environment and Resources Center Systems Development Institute University of Tennessee Knoxville TN USA High Performance Computing Laboratory Department of Computer Science Northern Illinois University Dekalb IL USA

The authors present a metacomputing application of multivariate, nonhierarchical statistical clustering to geographic environmental data from the 48 conterminous United States in order to produce maps of regions of ecological similarity, called ecoregions. These maps represent finer scale regionalizations than do those generated by the traditional technique: an expert with a marker pen. Several variables (e.g., temperature, organic matter, rainfall etc.) thought to affect the growth of vegetation are clustered at resolutions as fine as one square kilometer (1 km2). These data can represent over 7.8 million map cells in an n-dimensional (n = 9 to 25) data space. A parallel version of the iterative statistical clustering algorithm is developed by the authors using the MPI (Message Passing Interface) message passing routines. The parallel algorithm uses a classical, self-scheduling, single-program, multiple data (SPMD) organization; performs dynamic load balancing for reasonable performance in heterogeneous metacomputing environments; and provides fault tolerance by saving intermediate results for easy restarts in case of hardware failure. The parallel algorithm was tested on various geographically distributed heterogeneous metacomputing configurations involving an IBM SP3TM, an IBM SP2TM, and two SGI Origin 2000TM ’s. The tests were performed with minimal code modification, and were made possible by GlobusTM (a metacomputing software toolkit) and the Globus-enabled version of MPI (MPICH-G). Our performance tests indicate that while the algorithm works reasonably well under the metacomputing environment for a moderate number of processors, the communication overhead can become prohibitive for large processor configurations.

关键词： Metacomputing Message passing Parallel algorithms Testing Temperature Vegetation mapping Clustering algorithms Iterative algorithms Load management Fault tolerance

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Multivariate geographic clustering in a metacomputing environment using Globus 99

Multivariate geographic clustering in a metacomputing enviro...

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Proceedings of the 1999 ACM/IEEE conference on Supercomputing

作者： G. Mahinthakumar Forrest M. Hoffman William W. Hargrove Nicholas T. Karonis Oak Ridge National Laboratory Center for Computational Sciences P.O. Box 2008 Oak Ridge TN Oak Ridge National Laboratory Environmental Sciences Division P.O. Box 2008 Oak Ridge TN University of Tennessee Energy Environment and Resources Center Systems Development Institute 10521 Research Drive Suite 100 Knoxville TN High Performance Computing Laboratory Department of Computer Science Northern Illinois University Dekalb IL

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A study of code reuse and sharing characteristics of Java applications 1

A study of code reuse and sharing characteristics of Java ap...

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1st Workshop on Workload Characterization, WWC 1998

作者： Conte, M.T. Trick, A.R. Gyllenhaal, J.C. Hwu, W.W. Department of Electrical and Computer Engineering Coordinated Science Laboratory Center for Reliable and High-performance Computing University of Illinois at Urbana-Champaign United States

ISBN: (纸本)0769504507

Presents a detailed characterization of Java application and applet workloads in terms of reuse and sharing of Java code at the program, class and method level. In order to expose more sharing opportunities, techniques for detecting code equivalence even in the presence of minor code changes or constant pool index differences) are also proposed and examined. The analyzed application workload consists of the recently released SPECjvm98 benchmarks, and the applet workload is derived from three extensive searches of the Internet between May 1997 and May 1998 using an enhanced Web crawler. Analysis of these workloads reveals several new code sharing and optimization opportunities. © 1998 IEEE.

关键词： Java programming language

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Efficient runtime thread management for the nano-threads programming model 12th

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10 Workshops held in conjunction with 12th International Parallel Symposium and 9th Symposium on Parallel and Distributed Processing, IPPS/SPDP 1998

作者： Nikolopoulos, Dimitrios S. Polychronopoulos, Eleftherios D. Papatheodorou, Theodore S. High Performance Computing Architectures Laboratory Department of Computer Engineering and Informatics University of Patras Rio Patras26500 Greece

ISBN: (纸本)3540643591

The nano-threads programming model was proposed to effectively integrate multiprogramming on shared-memory multiprocessors, with the exploitation of fine-grain parallelism from standard applications. A prerequisite for the applicability of the nano-threads programming model is the ability of the runtime environment to manage parallelism at any level of granularity with minimal overheads. In this paper, we introduce runtime techniques for efficient memory management and user-level scheduling in an experimental runtime system designed to support the nano-threads programming model. We evaluate the exploitation of processor affinity for the management of nano-thread contexts, and the use of hierarchical queues to implement user-level scheduling strategies for applications with inherent multilevel parallelism. The proposed mechanisms attempt to obtain maximum benefits from data locality on cache-coherent NUMA multip'rocessors. Through the use of synthetic benchmarks, we find that our mechanism for memory management in the runtime system reduces overheads by 52% on average, compared to other known mechanisms. The use of hierarchical queues gives significant performance improvements between 17% and 40%, compared to scheduling strategies that use local queues. © Springer-Verlag Berlin Heidelberg 1998.

关键词： Multiprogramming

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Enhancing the performance of autoscheduling in Distributed Shared Memory multiprocessors

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4th International Conference on Parallel Processing, Euro-Par 1998

ISBN: (纸本)3540649522

Autoscheduling is a parallel program compilation and execution model that combines uniquely three features: Automatic extraction of loop and functional parallelism at any level of granularity, dynamic scheduling of parallel tasks, and dynamic program adaptability on multi-programmed shared memory multiprocessors. This paper presents a technique that enhances the performance of autoscheduling in Distributed Shared Memory (DSM) multiprocessors, targetting mainly at medium and large scale systems, where poor data locality and excessive communication impose performance bottlenecks. Our technique partitions the application Hierarchical Task Graph and maps the derived partitions to clusters of processors in the DSM architecture. Autoscheduling is then applied separately for each partition to enhance data locality and reduce communication costs. Our experimental results show that partitioning achieves remarkable performance improvements compared to a standard autoscheduling environment and a commercial parallelizing compiler.

关键词： Large scale systems

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A grid-enabled MPI: Message passing in heterogeneous distributed computing systems

A grid-enabled MPI: Message passing in heterogeneous distrib...

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1998 ACM/IEEE Conference on Supercomputing, SC 1998

作者： Foster, Ian Karonis, Nicholas T. Mathematics and Computer Science Division Argonne National Laboratory ArgonneIL60439 United States High-Performance Computing Laboratory Department of Computer Science Northern Illinois University DeKalbIL60115 United States

ISBN: (纸本)081868707X

Application development for high-performance distributed computing systems, or computational grids as they are sometimes called, requires "grid-enabled" tools that hide mundane aspects of the heterogeneous grid environment without compromising performance. As part of an investigation of these issues, we have developed MPICH-G, a grid-enabled implementation of the Message Passing Interface (MPI) that allows a user to run MPI programs across multiple computers at different sites using the same commands that would be used on a parallel computer. This library extends the Argonne MPICH implementation of MPI to use services provided by the Globus grid toolkit. In this paper, we describe the MPICH-G implementation and present preliminary performance results. © 1998 IEEE.

关键词： Message passing

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