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Conference on computer Vision and Pattern Recognition (CVPR)

作者： L. Gorelick M. Galun E. Sharon R. Basri A. Brandt Department of Computer Science and Applied Math Weizmann Institute of Science Rehovot Israel Division of Applied Math Brown University Providence RI USA

Silhouettes contain rich information about the shape of objects that can be used for recognition and classification. We present a novel approach that allows us to reliably compute many useful properties of a silhouette. Our approach assigns for every internal point of the silhouette a value reflecting the mean time required for a random walk beginning at the point to hit the boundaries. This function can be computed by solving Poisson's equation, with the silhouette contours providing boundary conditions. We show how this function can be used to reliably extract various shape properties including part structure and rough skeleton, local orientation and aspect ratio of different parts, and convex and concave sections of the boundaries. In addition to this we discuss properties of the solution and show how to efficiently compute this solution using multi-grid algorithms. We demonstrate the utility of the extracted properties by using them for shape classification.

关键词： Shape Poisson equations Skeleton computer vision Boundary conditions Application software computer science Data mining Object recognition Belts

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An evaluation of Java's I/O capabilities for high-performance computing

An evaluation of Java's I/O capabilities for high-performanc...

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ACM 2000 Java Grande Conference

作者： Dickens, Phillip M. Thakur, Rajeev Illinois Institute of Technology 10 West 31st Street Chicago IL 60616 United States Math. and Computer Science Division Argonne National Laboratory Argonne IL 60439 United States

ISBN: (纸本)1581132883

Java is quickly becoming the preferred language for writing distributed applications because of its inherent support for programming on distributed platforms. In particular, Java provides compile-time and run-time security, automatic garbage collection, inherent support for multithreading, support for persistent objects and object migration, and portability. Given these significant advantages of Java, there is a growing interest in using Java for high-performance computing applications. To be successful in the high-performance computing domain, however, Java must have the capability to efficiently handle the significant I/O requirements commonly found in high-performance computing applications. While there has been significant research in high-performance I/O using languages such as C, C++, and Fortran, there has been relatively little research into the I/O capabilities of Java. In this paper, we evaluate the I/O capabilities of Java for high-performance computing. We examine several approaches that attempt to provide high-performance I/O - many of which are not obvious at first glance - and investigate their performance in both parallel and multithreaded environments. We also provide suggestions for expanding the I/O capabilities of Java to better support the needs of high-performance computing applications.

关键词： Java programming language

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Design and evaluation of a resource selection framework for Grid applications

Design and evaluation of a resource selection framework for ...

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International Symposium on High Performance Distributed Computing

作者： Chuang Liu Lingyun Yang I. Foster D. Angulo Department of Computer Science University of Chicago Chicago IL USA Math & Computer Science Division Argonne National Laboratory Argonne IL USA

While distributed, heterogeneous collections of computers ("Grids") can in principle be used as a computing platform, in practice the problems of first discovering and then organizing resources to meet application requirements are difficult. We present a general-purpose resource selection framework that addresses these problems by defining a resource selection service for locating Grid resources that match application requirements. At the heart of this framework is a simple, but powerful, declarative language based on a technique called set matching, which extends the Condor matchmaking framework to support both single-resource and multiple-resource selection. This framework also provides an open interface for loading application-specific mapping modules to personalize the resource selector. We present results obtained when this framework is applied in the context of a computational astrophysics application, Cactus. These results demonstrate the effectiveness of our technique.

关键词： Processor scheduling Distributed computing Application software Grid computing computer science Organizing computer applications Virtual machining Control systems Resource management

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Mutual Information based Minimum Spanning Trees Model for Selecting Discriminative Genes

Mutual Information based Minimum Spanning Trees Model for Se...

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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： Fang Zhou Jieyue He Wei Zhong School of Computer Science and Engineering South-East University Jiangsu China Division of Math and Computer Science University of South Carolina Spartanburg USA

Recent studies have shown that gene selection is a crucial technology in microarray data analysis as a result of its large number of genes and relatively small number of samples. Filter methods are fast convergent algorithms with low time complexity. However, filter methods neglect correlation among genes. Other methods for gene selection also have disadvantages. For example, the measurement used to calculate the correlation in other methods can not effectively reflect function similarity among genes, the time complexity will be high based on the whole gene set. Therefore, we propose a novel selection model called mutual information based minimum spanning trees (MIMST) which considers both gene interaction and complementary genes. In this new model, we first use filter methods to remove non-relevant genes, and then compute the interdependence of top-ranked genes. Finally, we construct MST to remove the redundant genes. The experiment results show that MIMST can find the smallest siMIMSTgnificant genes subset with higher classification accuracy compared with other methods.

关键词： Mutual information Filters Data analysis computer science Shape Data engineering Gene expression Signal to noise ratio Euclidean distance Helium

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Scalable heterogeneous programming tools

Scalable heterogeneous programming tools

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1995 Heterogeneous Computing Workshop, HCW 1994

作者： Chen, Song Eshaghian, Mary M. Freund, Richard F. Potter, Jerry L. Wu, Ying-Chieh Department of Computer and Information Science New Jersey Institute of Technology NewarkNJ07102 United States RDT and E Division Naval Command Control and Ocean Surveillance Center San DiegoCA92152 United States Department of Math. and Computer Science Kent State University KentOH44242 United States

ISBN: (纸本)0818655925

In this paper, we study the heterogeneous use of two programming paradigms for heterogeneous computing called Cluster-M and HAsC. Both paradigms can efficiently support heterogeneous networks by preserving a level of abstraction which does not include any architecture mapping details. Furthermore, they are both machine independent and hence are scalable. Unlike, almost all existing heterogeneous orchestration tools which are MIMD based, HAsC is based on the fundamental concepts of SIMD associative computing. HAsC models a heterogeneous network as a coarse grained associative computer and is designed to optimize the execution of problems with large ratios of computations to instructions. Ease of programming and execution speed, not the utilization of idle resources are the primary goals of HAsC. On the other hand, Cluster-M is a generic technique that can be applied to both coarse grained as well as fine grained networks. Cluster-M provides an environment for porting various tasks onto the machines in a heterogeneous suite such that resources utilization is maximized and the overall execution time is minimized. We illustrate how these two paradigms can be used together to provide an efficient medium for heterogeneous programming. Finally, their scalability is discussed. © 1994 IEEE.

关键词： Heterogeneous networks

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Service-oriented science: scaling the application and impact of eResearch (Abstract)

Service-oriented science: scaling the application and impact...

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IEEE International Conference on e-science and Grid Computing

作者： I. Foster Department of Computer Science University of Chicago Chicago IL USA Math & Computer Science Division Argonne National Laboratory Argonne IL USA

The importance of service-oriented architecture for science is widely recognized. Increasingly, scientific communities are making information tools accessible as services that clients can access over the network, without knowledge of their internal workings. In this way, tools formerly accessible only to the specialist can be made available to all. Equally importantly, new value-added services can be constructed that integrate other services to automate useful tasks. The value of such service-oriented science has been demonstrated in disciplines as diverse as astronomy, biology, and fusion science. The mechanisms required to achieve these goals are provided, in part, by grid infrastructure. I review the mechanisms that have been developed to date for grid infrastructure and experience gained implementing these mechanisms, for example within the open source Globus Toolkit version 4. I present a range of dynamic service deployment scenarios, in which for example the TeraGrid and Open science Grid are used to host services for science communities. I discuss how these scenarios demonstrate the potential for scaling service-oriented science

关键词： Grid computing computer science Application software Bioinformatics Laboratories Service oriented architecture Astronomy Biology Robustness Economies of scale

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Decoupling computation and data scheduling in distributed data-intensive applications

Decoupling computation and data scheduling in distributed da...

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International Symposium on High Performance Distributed Computing

作者： K. Ranganathan I. Foster Department of Computer Science University of Chicago Chicago IL USA Math and Computer Science Division Argonne National Laboratory Argonne IL USA

In high-energy physics, bioinformatics, and other disciplines, we encounter applications involving numerous, loosely coupled jobs that both access and generate large data sets. So-called Data Grids seek to harness geographically distributed resources for such large-scale data-intensive problems. Yet effective scheduling in such environments is challenging, due to a need to address a variety of metrics and constraints while dealing with multiple, potentially independent sources of jobs and a large number of storage, compute, and network resources. We describe a scheduling framework that addresses these problems. Within this framework, data movement operations may be either tightly bound to job scheduling decisions or, alternatively, performed by a decoupled, asynchronous process on the basis of observed data access patterns and load. We develop a family of algorithms and use simulation studies to evaluate various combinations. Our results suggest that while it is necessary to consider the impact of replication, it is not always necessary to couple data movement and computation scheduling. Instead, these two activities can be addressed separately, thus significantly simplifying the design and implementation.

关键词： Distributed computing Processor scheduling Scheduling algorithm Application software computer science Large-scale systems Resource management Physics computing Laboratories Bioinformatics

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Distributed data provenance for large-scale data-intensive computing

Distributed data provenance for large-scale data-intensive c...

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IEEE International Conference on Cluster Computing

作者： Dongfang Zhao Chen Shou Tanu Maliky Ioan Raicu Department of Computer Science Illinois Institute of Technology Computation Institute The University of Chicago USA Math and Computer Science Division Argonne National Laboratory

It has become increasingly important to capture and understand the origins and derivation of data (its provenance). A key issue in evaluating the feasibility of data provenance is its performance, overheads, and scalability. In this paper, we explore the feasibility of a general metadata storage and management layer for parallel file systems, in which metadata includes both file operations and provenance metadata. We experimentally investigate the design optimality-whether provenance metadata should be loosely-coupled or tightly integrated with a file metadata storage systems. We consider two systems that have applied similar distributed concepts to metadata management, but focusing singularly on kind of metadata: (i) FusionFS, which implements a distributed file metadata management based on distributed hash tables, and (ii) SPADE, which uses a graph database to store audited provenance data and provides distributed module for querying provenance. Our results on a 32-node cluster show that FusionFS+SPADE is a promising prototype with negligible provenance overhead and has promise to scale to petascale and beyond. Furthermore, FusionFS with its own storage layer for provenance capture is able to scale up to 1 K nodes on BlueGene/P supercomputer.

关键词： Kernel Scalability Java Throughput

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Ergodic mutual information of OFDMA-based Selection-Decode-and-Forward cooperative relay networks with imperfect CSI

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Physical Communication 2009年第3期2卷 184-193页

作者： Awad, Mohamad Khattar Shen, Xuemin Zogheib, Bashar Department of Electrical and Computer Engineering University of Waterloo Waterloo Ont. N2L 3G1 Canada Division of Math Science and Technology Nova Southeastern University Fort Lauderdale FL 33314 United States

This paper presents a novel approach to investigate ergodic mutual information of OFDMA Selection-Decode-and-Forward (SDF) cooperative relay networks with imperfect channel state information (CSI). Relay stations are either dedicated or non-dedicated (i.e., subscriber stations assisting other subscriber stations). The CSI imperfection is modeled as an additive random variable with known statistics. Numerical evaluations and simulations demonstrate that by considering the CSI imperfection based on a priori knowledge of the estimation error statistics, a substantial gain can be achieved in terms of ergodic mutual information which makes channel adaptive schemes closer to practical implementations. © 2009 Elsevier B.V. All rights reserved.

关键词： Channel estimation Imperfect CSI OFDMA networks SDF cooperative relay networks

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Graph-Based Multilevel Dimensionality Reduction with Applications to Eigenfaces and Latent Semantic Indexing

Graph-Based Multilevel Dimensionality Reduction with Applica...

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International Conference on Machine Learning and Applications (ICMLA)

作者： Sophia Sakellaridi Haw-ren Fang Yousef Saad Computer Science & Engineering Department University of Minnesota Minneapolis MN USA Math & Computer Science Division Argonne National Laboratory Argonne IL USA

Dimension reduction techniques have been successfully applied to face recognition and text information retrieval. The process can be time-consuming when the data set is large. This paper presents a multilevel framework to reduce the size of the data set, prior to performing dimension reduction. The algorithm exploits nearest-neighbor graphs. It recursively coarsens the data by finding a maximal matching level by level. The coarsened data at the lowest level is then projected using a known linear dimensionality reduction method. The same linear mapping is performed on the original data set, and on any new test data. The methods are illustrated on two applications: eigenfaces (face recognition) and latent semantic indexing (text mining). Experimental results indicate that the multilevel techniques proposed here offer a very appealing cost to quality ratio.

关键词： Indexing Face recognition Text mining Information retrieval Traveling salesman problems Sampling methods Machine learning Laboratories Performance evaluation Testing

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