检索结果-内蒙古大学图书馆

Parallel discrete event simulation on desktop grid computing infrastructures

International Journal of Simulation and Process Modelling 2009年第2期5卷 157-171页

作者： Park, Alfred Fujimoto, Richard M. Computational Science and Engineering Division College of Computing Georgia Institute of Technology 266 Ferst Drive Atlanta GA 30332-0765 United States

In contrast to traditional Parallel Discrete Event Simulation (PDES) systems using dedicated machines, an alternative master/worker approach for high throughput execution on shared computing platforms is proposed. Master/worker systems offer potential advantages over traditional PDES systems such as better support for heterogeneous machines, client-driven load balancing, fault tolerance, and execution on non-dedicated machines. We examine feasibility of executing PDES codes on master/ worker systems. We characterise application properties that are important for efficient execution and define suitable performance metrics. The Aurora Parallel and Distributed Simulation System utilising the master/worker approach is described along with performance measurements in executing conservative PDES codes. Copyright © 2009, Inderscience Publishers.

关键词： Fault tolerance

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Ad Hoc distributed dynamic data-driven simulations of surface transportation systems

Ad Hoc distributed dynamic data-driven simulations of surfac...

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作者： Hunter, Michael Kim, Hoe Kyoung Suh, Wonho Fujimoto, Richard Sirichoke, Jason Palekar, Mahesh School of Civil and Environmental Engineering Georgia Institute of Technology Atlanta GA United States Computational Science and Engineering Division College of Computing Georgia Institute of Technology Atlanta GA United States Hewlett Packard StorageWorks Division Colorado Springs CO United States Google Inc Mountain View CA United States

An ad hoc distributed dynamic data-driven simulation is a collection of autonomous online simulations brought together to model an operational system. They offer the potential of increased accuracy, responsiveness, and robustness compared to centralized approaches. They differ from conventional distributed simulations in that they are created bottom-up rather than top-down. They combine concepts from conventional distributed simulations and replicated trials, raising new issues in data management and synchronization. In this article, the ad hoc simulation approach and an optimistic synchronization algorithm are proposed. A prototype coupling in-vehicle transportation simulation is evaluated and shown to yield results comparable to a traditional replicated experiment for the tested scenarios. Experiences applying this concept to a commercial transportation simulator in an emergency scenario are described. © 2009 The Society for Modeling and Simulation International.

关键词： Information management

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Enhancing diversity, coverage and balance for summarization through structure learning 09

Enhancing diversity, coverage and balance for summarization ...

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18th International World Wide Web Conference, WWW 2009

作者： Li, Liangda Zhou, Ke Xue, Gui-Rong Zha, Hongyuan Yu, Yong Dept. of Computer Science and Engineering Shanghai Jiao-Tong University No. 800 Dongchuan Road Shanghai 200240 China College of Computing Georgia Institute of Technology Atlanta GA 30032 United States

ISBN: (纸本)9781605584874

Document summarization plays an increasingly important role with the exponential growth of documents on the Web. Many supervised and unsupervised approaches have been proposed to generate summaries from documents. However, these approaches seldom simultaneously consider summary diversity, coverage, and balance issues which to a large extent determine the quality of summaries. In this paper, we consider extract-based summarization emphasizing the following three requirements: 1) diversity in summarization, which seeks to reduce redundancy among sentences in the summary;2) sufficient coverage, which focuses on avoiding the loss of the document's main information when generating the summary;and 3) balance, which demands that different aspects of the document need to have about the same relative importance in the summary. We formulate the extract-based summarization problem as learning a mapping from a set of sentences of a given document to a subset of the sentences that satisfies the above three requirements. The mapping is learned by incorporating several constraints in a structure learning framework, and we explore the graph structure of the output variables and employ structural SVM for solving the resulted optimization problem. Experiments on the DUC2001 data sets demonstrate significant performance improvements in terms of F1 and ROUGE metrics. Copyright is held by the International World Wide Web Conference Committee (IW3C2).

关键词： Mapping

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Qilin: Exploiting parallelism on heterogeneous multiprocessors with adaptive mapping 42

Qilin: Exploiting parallelism on heterogeneous multiprocesso...

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42nd Annual IEEE/ACM International Symposium on Microarchitecture, Micro-42

作者： Luk, Chi-Keung Hong, Sunpyo Kim, Hyesoon Software Pathfinding and Innovations Software and Services Group Intel Corporation Hudson MA 01749 United States Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA 30332 United States College of Computing School of Computer Science Georgia Institute of Technology Atlanta GA 30332 United States

ISBN: (纸本)9781605587981

Heterogeneous multiprocessors are increasingly important in the multi-core era due to their potential for high performance and energy efficiency. In order for software to fully realize this potential, the step that maps computations to processing elements must be as automated as possible. However, the state-of-the-art approach is to rely on the programmer to specify this mapping manually and statically. This approach is not only labor intensive but also not adaptable to changes in runtime environments like problem sizes and hardware/software configurations. In this study, we propose adaptive mapping, a fully automatic technique to map computations to processing elements on a CPU+GPU machine. We have implemented it in our experimental heterogeneous programming system called Qilin. Our results show that, by judiciously distributing works over the CPU and GPU, automatic adaptive mapping achieves a 25% reduction in execution time and a 20% reduction in energy consumption than static mappings on average for a set of important computation benchmarks. We also demonstrate that our technique is able to adapt to changes in the input problem size and system configuration. Copyright 2009 ACM.

关键词： Mapping

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Efficient GSVD Based Multi-User MIMO Linear Precoding and Antenna Selection Scheme

Efficient GSVD Based Multi-User MIMO Linear Precoding and An...

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IEEE International Conference on Communications (ICC)

作者： J. Park J. Chun H. Park Division of Electrical Engineering School of Electrical Engineering and Computer Science Korea Advanced Institute of Science and Technology Daejeon South Korea Division of Computational Science and Engineering College of Computing Georgia Institute of Technology Atlanta GA USA

We present a multi-user multiple-input multiple-output (MU-MIMO) preceding scheme utilizing generalized singular value decomposition (GSVD). Our work is motivated by the precoding scheme developed by Sadek, Tarighat, and Sayed that maximizes the signal to leakage and noise ratio (SLNR), in which the precoding weight is obtained by the generalized eigenvalue decomposition (GEVD). However, the covariance matrix utilized in GEVD becomes close to be singular as the signal to noise ratio goes high. To improve the numerical accuracy, a GSVD based algorithm is exploited in this paper and a novel method is derived to compute the precoding weights for multiple users by removing redundant computational loads rather than repeating the GSVD algorithm for each user. In addition, we propose a technique to speed up the GSVD based precoding algorithm by preprocessing using the QR decomposition. Finally, to improve the system performance, the antenna selection scheme using GSVD is also proposed which does not require the exhaustive search to choose the active antennas.

关键词： MIMO Receiving antennas Signal to noise ratio Covariance matrix Interference Linear discriminant analysis Transmitting antennas Matrix decomposition Paper technology Peer to peer computing

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Assessment of Gene Annotation Accuracy by Inferring Transcripts from RNA-Seq

Assessment of Gene Annotation Accuracy by Inferring Transcri...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Jeffrey Martin Wenhan Zhu Nicholas Bergman Mark Borodovsky School of Biology Georgia Institute of Technology Atlanta GA USA Wallace H. Coulter Department of Biomedical Engineering Computational Science and Engineering Division College of Computing Georgia Institute of Technology Atlanta GA USA

Next generation sequencing is quickly changing long standing paradigms of genomics in terms of what is feasible to accomplish within a ldquoresearch life timerdquo and what is supposed to remain beyond limits of reliable experimental analysis. Sequencing and mapping of a prokaryote transcriptome can provide experimental validation for computationally predicted genes annotated in a prokaryotic genome. In this study we use the transcriptome sequencing to assess the accuracy of the public annotation of genes in a genome of important pathogen Bacillus anthracis. We show that the transcriptome data confirm existence of a number of genes missing in the annotation. Also, the transcriptome data indicate that pseudogenes, genes with frameshifts and in frame stop codons, do keep the transcriptional activity (while possessing a coding potential as well) and continue to present a challenge for accurate annotation.

关键词： Bioinformatics Genomics Hidden Markov models Solids Biology computing Biomedical engineering RNA Gene expression Systems biology Laboratories

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LITSEEK: Public health Literature Search by metadata enhancement with External Knowledge bases

LITSEEK: Public health Literature Search by metadata enhance...

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3rd ACM International Workshop on Data and Text Mining in Bioinformatics, DTMBIO'09, Co-located with the 18th ACM International Conference on Information and Knowledge Management, CIKM 2009

作者： Prabhu, Priyanka Sharad Navathe, Shamkant B. Tyler, Stephen Dasigi, Venu Narkhede, Neha Palanisamy, Balaji College of Computing Georgia Institute of Technology Atlanta GA 30332-0280 United States Dept. of Computer Science and Software Engineering Southern Polytechnic State University Marietta GA 30060-2855 United States

ISBN: (纸本)9781605588032

Biomedical literature is an important source of information in any researcher's investigation of genes, risk factors, diseases and drugs. Often the information searched by public health researchers is distributed across multiple disparate sources that may include publications from PubMed, genomic, proteomic and pathway databases, gene expression and clinical resources and biomedical ontologies. The unstructured nature of this information makes it difficult to find relevant parts from it manually and comprehensive knowledge is further difficult to synthesize automatically. In this paper we report on LITSEEK (LITerature Search by metadata Enhancement with External Knowledgebases), a system we have developed for the benefit of researchers at the Centers for Disease Control (CDC) to enable them to search the HuGE (Human Genome for Epidemiology) database of PubMed articles, from a pharmacogenomic perspective. Besides analyzing text using TFIDF ranking and indexing of the important terms, the proposed system incorporates an automatic consultation with PharmGKB - a human-curated knowledge base about drugs, related diseases and genes, as well as with the Gene Ontology, a human-curated, well accepted ontology. We highlight the main components of our approach and illustrate how the search is enhanced by incorporating additional concepts in terms of genes/drugs/diseases (called metadata for ease of reference) from PharmGKB. Various measurements are reported with respect to the addition of these metadata terms. Preliminary results in terms of precision based on expert user feedback from CDC are encouraging. Further evaluation of the search procedure by actual researchers is under way. Copyright 2009 ACM.

关键词： Metadata

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Multi-task learning for learning to rank in web search

Multi-task learning for learning to rank in web search

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ACM 18th International Conference on Information and Knowledge Management, CIKM 2009

作者： Bai, Jing Zhou, Ke Xue, Guirong Zha, Hongyuan Sun, Gordon Tseng, Belle Zheng, Zhaohui Chang, Yi Yahoo Labs. 701 First Avenue Sunnyvale CA United States Dept. of Computer Science and Engineering Shanghai Jiao-Tong University China College of Computing Georgia Institute of Technology Atlanta GA United States

ISBN: (纸本)9781605585123

Both the quality and quantity of training data have significant impact on the performance of ranking functions in the context of learning to rank for web search. Due to resource constraints, training data for smaller search engine markets are scarce and we need to leverage existing training data from large markets to enhance the learning of ranking function for smaller markets. In this paper, we present a boosting framework for learning to rank in the multi-task learning context for this purpose. In particular, we propose to learn non-parametric common structures adaptively from multiple tasks in a stage-wise way. An algorithm is developed to iteratively discover super-features that are effective for all the tasks. The estimation of the functions for each task is then learned as a linear combination of those super-features. We evaluate the performance of this multi-task learning method for web search ranking using data from a search engine. Our results demonstrate that multi-task learning methods bring significant relevance improvements over existing baseline methods. Copyright 2009 ACM.

关键词： Function evaluation

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Faster FAST: Multicore acceleration of streaming financial data

Faster FAST: Multicore acceleration of streaming financial d...

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作者： Agarwal, Virat Bader, David A. Dan, Lin Liu, Lurng-Kuo Pasetto, Davide Perrone, Michael Petrini, Fabrizio IBM TJ Watson Center 1101 Kitchawan Road Route 134 Yorktown Heights NY 10598 United States College of Computing Georgia Institute of Technology Atlanta GA 30332 United States IBM Computational Science Center Damastown Industrial Estate Mulhuddart Dublin Ireland

By 2010, the global options and equity markets will average over 128 billion messages per day, amounting to trillions of dollars in trades. Trading systems, the backbone of the low-latency high-frequency business, need fundamental research and innovation to overcome their current processing bottlenecks. With market data rates rapidly growing, the financial community is demanding solutions that are extremely fast, flexible, adaptive, and easy to manage. This paper explores multiple avenues to deal with the decoding and normalization of Option Price Reporting Authority (OPRA) stock market data feeds encoded with FIX Adapted for Streaming (FAST) representation, on commodity multicore platforms, and describes a novel solution that encodes the OPRA protocol with a high-level description language. Our algorithm achieves a processing rate of 15 million messages per second in the fastest single socket configuration on an Intel Xeon E5472, which is an order of magnitude higher than the current needs of the financial systems. We also present an in-depth performance evaluation that exposes important properties of our OPRA parsing algorithm on a collection of multicore processors. © 2009 Springer-Verlag.

关键词： Financial markets

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Adaptive CPG based coordinated control of healthy and robotic lower limb movements

Adaptive CPG based coordinated control of healthy and roboti...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Jae-Kwan Ryu Nak Young Chong Bum Jae You Henrik Christensen Mechanical Engineering Research and Development Laboratory Gyeonggi South Korea School of Information Science Japan Advanced Institute of Science and Technology Ishikawa Japan Center of Cognitive Robotics Research Korea Institute of Science and Technology Seoul South Korea College of Computing Georgia Institute of Technology Atlanta GA USA

This paper proposes an adaptive CPG based controller for a lower limb prosthesis consisting of online trajectory generation and interlimb coordination. The adaptive CPG can produce multidimensional rhythmic patterns and modulate their frequency by tuning relevant parameters in an autonomously way adapting to a changing periodicity of external signals. Also, to increase the stability of the prosthesis, a spring-damper component is attached between the hip and ankle joints, allowing the absorption of impulsive ground reaction forces at landing. We verify the validity of the proposed controller with a simulated humanoid robot through the investigation of the self-coordination between the healthy and robotic legs.

关键词： Programmable control Adaptive control Robot kinematics Prosthetics Humanoid robots Multidimensional systems Frequency modulation Tuning Stability Hip

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