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International Conference on Data Engineering Workshops

作者： S. Bowers B. Ludascher A.H.H. Ngu T. Critchlow UC Davis Genome Center University of California Davis USA Department of Computer Science UC Davis Genome Center University of California Davis USA Department of Computer Science Texas State University San Marcos San Marcos USA Center for Applied Scientific Computing Lawrence Livemore National Laboratory USA

Data-centric scientific workflows are often modeled as dataflow process networks. The simplicity of the dataflow framework facilitates workflow design, analysis, and optimization. However, modeling "control-flow intensive" tasks using dataflow constructs often leads to overly complicated workflows that are hard to comprehend, reuse, and maintain. We describe a generic framework, based on scientific workflow templates and frames, for embedding control-flow intensive subtasks within dataflow process networks. This approach can seamlessly handle complex control-flow without sacrificing the benefits of dataflow. We illustrate our approach with a real-world scientific workflow from the astrophysics domain, requiring remote execution and file transfer in a semi-reliable environment. For such workflows, we also describe a 3-layered architecture based on frames and templates where the top-layer consists of an overall dataflow process network, the second layer consists of a tranducer template for modeling the desired control-flow behavior, and the bottom layer consists of frames inside the template that are specialized by embedding the desired component implementation. Our approach can enable scientific workflows that are more robust (faulttolerance strategies can be defined by control-flow driven transducer templates) and at the same time more reusable, since the embedding of frames and templates yields more structured and modular workflow designs.

关键词： Mathematical model Processor scheduling Data structures Genomics Bioinformatics computer science Robust control Data engineering scientific computing Laboratories

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Quadruped robot obstacle negotiation via reinforcement learning

Quadruped robot obstacle negotiation via reinforcement learn...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Honglak Lee Yirong Shen Chih-Han Yu G. Singh A.Y. Ng Stanford University Stanford CA US Department of Electrical Engineering University of Stanford Stanford CA USA Scientific Computing and Computational Mathematics Program University of Stanford Stanford CA USA Computer Science Department University of Stanford Stanford CA USA

Legged robots can, in principle, traverse a large variety of obstacles and terrains. In this paper, we describe a successful application of reinforcement learning to the problem of negotiating obstacles with a quadruped robot. Our algorithm is based on a two-level hierarchical decomposition of the task, in which the high-level controller selects the sequence of foot-placement positions, and the low-level controller generates the continuous motions to move each foot to the specified positions. The high-level controller uses an estimate of the value function to guide its search; this estimate is learned partially from supervised data. The low-level controller is obtained via policy search. We demonstrate that our robot can successfully climb over a variety of obstacles which were not seen at training time

关键词： Learning Robot kinematics Legged locomotion Foot Mobile robots Leg Motion control Robotics and automation Path planning computer science

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Parallel PDE-based simulations using the common component architecture

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Lecture Notes in Computational science and Engineering 2006年 51卷 327-381页

作者： McInnes, Lois Curfman Allan, Benjamin A. Armstrong, Robert Benson, Steven J. Bernholdt, David E. Dahlgren, Tamara L. Diachin, Lori Freitag Krishnan, Manojkumar Kohl, James A. Walter Larson, J. Lefantzi, Sophia Nieplocha, Jarek Norris, Boyana Parker, Steven G. Ray, Jaideep Zhou, Shujia Mathematics and Computer Science Division Argonne National Laboratory Argonne IL United States Livermore CA United States Computer Science and Mathematics Division Oak Ridge National Laboratory Oak Ridge TN United States Center for Applied Scientific Computing Lawrence Livermore National Laboratory Livermore CA United States Computational Sciences and Mathematics Pacific Northwest National Laboratory Richland WA United States Reacting Flow Research SNL Livermore CA United States Scientific Computing and Imaging Institute University of Utah Salt Lake City UT United States Advanced Software R and D SNL Livermore CA United States Northrop Grumman Corporation Information Technology Sector Chantilly VA United States

ISBN: (纸本)9783540290766

The complexity of parallel PDE-based simulations continues to increase as multimodel, multiphysics, and multi-institutional projects become widespread. A goal of component - based software engineering in such large-scale simulations is to help manage this complexity by enabling better interoperability among various codes that have been independently developed by different groups. The Common Component Architecture (CCA) Forum is defining a component architecture specification to address the challenges of high-performance scientific computing. In addition, several execution frameworks, supporting infrastructure, and general-purpose components are being developed. Furthermore, this group is collaborating with others in the high-performance computing community to design suites of domain-specific component interface specifications and underlying implementations. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Multiphysics

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Heuristics for estimating contact area of supports in layered manufacturing

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ACM Journal of Experimental Algorithmics 2006年 11卷 1.6–es页

作者： Ilinkin, Ivayio Janardan, Ravi Smid, Michiel Johnson, Eric Castillo, Paul Schwerdt, Jörg Department of Mathematics and Computer Science Rhodes College Memphis 38112 TN United States Department of Computer Science and Engineering University of Minnesota Minneapolis 55455 MN United States School of Computer Science Carleton University Ottawa K1S 5B6 ON Canada Center for Applied Scientific Computing Lawrence Livermore National Laboratory Livermore 94551 CA United States Softwarebüro Bubel GmbH Kirkel 66459 Germany

Layered manufacturing is a technology that allows physical prototypes of three-dimensional(3D) models to be built directly from their digital representation, as a stack of two-dimensional(2D) layers. A key design problem here is the choice of a suitable direction in which the digital model should be oriented and built so as to minimize the area of contact between the prototype and temporary support structures that are generated during the build. Devising an efficient algorithm for computing such a direction has remained a difficult problem for quite some time. In this paper, a suite of efficient and practical heuristics is presented for estimating the minimum contact area. Also given is a technique for evaluating the quality of the estimate provided by any heuristic, which does not require knowledge of the (unknown and hard-to-compute) optimal solution;instead, it provides an indirect upper bound on the quality of the estimate via two relatively easy-to-compute quantities. The algorithms are based on various techniques from computational geometry, such as ray-shooting, convex hulls, boolean operations on polygons, and spherical arrangements, and have been implemented and tested. Experimental results on a wide range of real-world models show that the heuristics perform quite well in practice. © 2006 ACM.

关键词： Algorithm implementation and testing Algorithms Computational geometry E.1 [Data structures] Experimentation F.2.2 [Analysis of algorithms and problem complexity]: Nonnumerical algorithms and problems I.6 [computer-aided engineering] Measurement Performance Theory

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Automatic Differentiation: Applications, Theory, and Implementations

Lecture Notes in Computational Science and Engineering

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Lecture Notes in Computational science and Engineering 2006年 50卷

作者： Bücker, Martin Corliss, George Hovland, Paul Naumann, Uwe Norris, Boyana Institute for Scientific Computing RWTH Aachen University D-52056 Aachen Germany Department of Electrical and Computer Engineering Marquette University 1515 W. Wisconsin Avenue P.O. Box 1881 Milwaukee WI 53201-1881 United States Software and Tools for Computational Engineering RWTH Aachen University D-52056 Aachen Germany Mathematics and Computer Science Division Argonne National Laboratory 9700 S Cass Ave Argonne IL 60439 United States

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Predicting the electronic properties of 3D, million-atom semiconductor nanostructure architectures

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Journal of Physics: Conference Series 2006年第1期46卷

作者： A Zunger A Franceschetti G Bester W B Jones Kwiseon Kim P A Graf L-W Wang A Canning O Marques C Voemel J Dongarra J Langou S Tomov Materials Science Center NREL USA Scientific Computing Center NREL USA Computational Research Division LBNL USA Department of Computer Science University of Tennessee USA

The past ~10 years have witnessed revolutionary breakthroughs both in synthesis of quantum dots (leading to nearly monodispersed, defect-free nanostructures) and in characterization of such systems, revealing ultra narrow spectroscopic lines of <1 meV width, exposing new intriguing effects, such as multiple exciton generation, fine-structure splitting, quantum entanglement, multiexciton recombination and more. These discoveries have led to new technological applications including quantum computing and ultra-high efficiency solar cells. Our work in this project is based on two realizations/observations: First, that the dots exhibiting clean and rich spectroscopic and transport characteristics are rather big. Indeed, the phenomenology indicated above is exhibited only by the well-passivated defect-free quantum dots containing at least a few thousand atoms (colloidal) and even a few hundred thousand atoms (self assembled). Understanding the behavior of nanotechnology devices requires the study of even larger, million-atom systems composed of multiple components such as wires+dots+films. Second, first-principles many-body computational techniques based on current approaches (Quantum Monte-Carlo, GW, Bethe-Salpeter) are unlikely to be adaptable to such large structures and, at the same time, the effective mass-based techniques are too crude to provide insights on the many-body/atomistic phenomenology revealed by experiment. Thus, we have developed a set of methods that use an atomistic approach (unlike effective-mass based techniques) and utilize single-particle + many body techniques that are readily scalable to ~103−106 atom nanostructures. New mathematical and computational techniques have also been developed to accelerate our calculations and go beyond simple conjugate gradient based methods allowing us to study larger systems. In this short paper based on a poster presented at the DOE SciDAC06 conference we will present the overall structure as well as highlights of

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Accelerating the scientific exploration process with scientific workflows

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Journal of Physics: Conference Series 2006年第1期46卷

作者： Ilkay Altintas Oscar Barney Zhengang Cheng Terence Critchlow Bertram Ludaescher Steve Parker Arie Shoshani Mladen Vouk San Diego Supercomputer Center University of California San Diego USA Scientific Computing and Imaging Institute University of Utah USA Department of Computer Science North Carolina State University USA Center for Applied Scientific Computing Lawrence Livermore National Laboratory USA Department of Computer Science University of California Davis USA Computing Research Division Lawrence Berkeley National Laboratory USA

Although an increasing amount of middleware has emerged in the last few years to achieve remote data access, distributed job execution, and data management, orchestrating these technologies with minimal overhead still remains a difficult task for scientists. scientific workflow systems improve this situation by creating interfaces to a variety of technologies and automating the execution and monitoring of the workflows. Workflow systems provide domain-independent customizable interfaces and tools that combine different tools and technologies along with efficient methods for using them. As simulations and experiments move into the petascale regime, the orchestration of long running data and compute intensive tasks is becoming a major requirement for the successful steering and completion of scientific investigations. A scientific workflow is the process of combining data and processes into a configurable, structured set of steps that implement semi-automated computational solutions of a scientific problem. Kepler is a cross-project collaboration, co-founded by the SciDAC scientific Data Management (SDM) Center, whose purpose is to develop a domain-independent scientific workflow system. It provides a workflow environment in which scientists design and execute scientific workflows by specifying the desired sequence of computational actions and the appropriate data flow, including required data transformations, between these steps. Currently deployed workflows range from local analytical pipelines to distributed, high-performance and high-throughput applications, which can be both data- and compute-intensive. The scientific workflow approach offers a number of advantages over traditional scripting-based approaches, including ease of configuration, improved reusability and maintenance of workflows and components (called actors), automated provenance management, ''smart'' re-running of different versions of workflow instances, on-the-fly updateable parameters, monitoring

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Random beamforming in MIMO systems exploiting efficient multiuser diversity

Random beamforming in MIMO systems exploiting efficient mult...

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2005 IEEE 61st Vehicular Technology Conference -VTC 2005 - Spring Stockholm: Paving the Path for a Wireless Future

作者： Kim, Eun Yong Chun, Joohwan Scientific Computing Lab. Department of Electrical Engineering and Computer Science Korea Advanced Institute of Science and Technology Daejeon Korea Republic of

We propose a new random beamforming technique in forward link multiuser MIMO systems that exploits efficient multiuser diversity and spatial multiplexing gain. The common channels are allocated to more than one user simultaneously and multiple antennas at the receivers are used for interference nulling, resulting in higher throughput and reduced average waiting time. We show that the throughput of the proposed scheme outperforms the upper bound of the conventional scheme. © 2005 IEEE.

关键词： Communication channels (information theory)

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Online particle size estimation on one-pass edge detection and particle shape

Online particle size estimation on one-pass edge detection a...

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International Conference on Machine Learning and Cybernetics, ICMLC 2005

作者： Wang, Wei-Xing Bergholm, Fredrik Department of Computer Science and Technology Chongqing University of Posts and Telecommunications 400065 China Department of Scientific Computing Uppsala University Sweden

ISBN: (纸本)078039092X

In order to quickly and accurately estimate average size of densely packed aggregate particles on a moving conveyor belt, a new image processing method is studied, the method consists of the two major algorithms, the one is one-pass edge detection algorithm, and the other is the average size estimation based on image edge density. The method calculates average particle size without explicit delineating complicated aggregates. To prove the new method, two different aggregate samples were taken for testing, the testing result is satisfactory. The new method is much fast than ordinary particle segmentation algorithm, and is applicable for the image sequence of the densely packed complicated particles. ©2005 IEEE.

关键词： Edge detection

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Data redistribution and remote method invocation in parallel component architectures

Data redistribution and remote method invocation in parallel...

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19th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2005

作者： Bertrand, Felipe Bramley, Randall Bernholdt, David E. Kohl, James A. Sussman, Alan Larson, Jay W. Damevski, Kostadin B. Indiana University Computer Science Department Oak Ridge National Laboratory Computer Science and Mathematics Division University of Maryland UMIACS Department of Computer Science Argonne National Laboratory Mathematics and Computer Science Division University of Utah Scientific Computing and Imaging Institute

ISBN: (纸本)0769523129

With the increasing availability of high-performance massively parallel computer systems, the prevalence of sophisticated scientific simulation has grown rapidly. The complexity of the scientific models being simulated has also evolved, leading to a variety of coupled multi-physics simulation codes. Such cooperating parallel programs require fundamentally new interaction capabilities, to efficiently exchange parallel data structures and collectively invoke methods across programs. So-called "M×N" research, as part of the Common Component Architecture (CCA) effort, addresses these special and challenging needs, to provide generalized interfaces and tools that support flexible parallel data redistribution and parallel remote method invocation. Using this technology, distinct simulation codes with disparate distributed data decompositions can work together to achieve greater scientific discoveries.

关键词： Parallel processing systems

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