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Approaches to obtain a large number of ranked solutions to 3-dimensional assignment problems

Journal of Advances in Information Fusion 2018年第1期13卷 50-67页

作者： Zhang, Lingyi Sidoti, David Vallabhaneni, Spandana Pattipati, Krishna R. Castañoń, David A. Department of Electrical and Computer Engineering University of Connecticut StorrsCT06269 United States Boston University BostonMA02215 United States

A generalized 3-dimensional assignment problem is a decisionmaking process that involves allocating limited resources to a set of tasks over time, where the objective is to optimize a cost function subject to a set of generalized assignment constraints. The 3- dimensional (3-D) assignment problems are known to be NP-hard. In this paper, we propose a novel approach to efficiently solve an m-best 3-D assignment problem with non-unity right-hand side constraints (also referred to simply as 3-D assignment problem), where m may be large (as many as 104 solutions), by decomposing it into two sequential phases. In phase I, we partition the original problem space into a series of subproblems via Murty's m-best search space decomposition procedure. Modifications previously proposed in the literature for the 2-dimensional (2-D) assignment problem are applied to optimize the search space decomposition for the 3- D assignment problem. In phase II, we solve each subproblem by using Lagrangian relaxation and solving the 3-D assignment problem as a combination of relaxed 2-D assignment problems and 2-D transportation problems. The 2-D assignment problem is solved by the JVC or auction algorithms, and the 2-D transportation problem is solved by the simplex-based transportation, Transauction or RELAX-IV algorithms. The sequence of relaxed 2-D problems are interchangeable, while adhering to the relaxed constraints. We validate and compare the performance and utility of the proposed algorithms and search space decomposition optimizations via extensive numerical experiments. Overall, the fully optimized algorithm took less than 50 seconds, on average, to obtain 104 soutions for a tensor of dimension 30×30×8. © 2018 International Society of Information Fusion. All rights reserved.

关键词： Cost functions

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Chunk-wise parallelization based on dynamic performance prediction on heterogeneous Multicores 15

Chunk-wise parallelization based on dynamic performance pred...

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15th International conference on high performance Computing & Simulation (HPCS)

作者： Dab, Asma Slama, Yosr Tunis El Manar Univ Fac Sci Dept Informat Tunis Tunisia

ISBN: (纸本)9781538632505

Multicore machines are becoming more and more common. Ideally, all applications benefit from these advances in computer architecture. A complex challenge in parallel computing is cores load balancing to minimize the overall execution time called Makespan of the parallel program. As multicores may have different architectures, an effective mapping should support this unknown variation to avoid drawbacks on makespan. In fact, mapping or static load balancing method may not be effective when the target state machine changes during program execution. Thread affinity has appeared as an important technique to improve the program performance and for better performance stability. In this context, we propose a predictive approach using iterations chunking at runtime allowing parallel code adaptation to processor's performance. Our approach is based on thread pinning and performance detection at execution time. From a parallel program, we define a set of loop nest iterations, forming what is called chunk, and we run it using a first mapping assuming homogeneous cores. Then, performance assessment would correct mapping by speculating the future core's state. The new mapping would be then applied to a new chunk for further evaluation and prediction. The process would stop when the program is fully executed or when judging that chunking is no longer effective.

关键词： component Automatic parallelization Chunk Load balancing Mapping Multicores Speculation Thread affinity Thread level parallelism Polyhedron program Prediction

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Advances in Supercomputer Optimization of RF Devices 18

Advances in Supercomputer Optimization of RF Devices

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18th International Vacuum Electronics conference (IVEC)

作者： Jensen, Aaron Petillo, John Ovtchinnikov, Serguei Burke, Alex Panagos, Dimitrios Kostas, Chris Stantchev, George Cooke, Simon Leidos Inc Billerica MA 01821 USA US Naval Res Lab Washington DC 20375 USA

ISBN: (纸本)9781509059164

An integrated environment for large scale multi-parameter design optimization of RF devices is presented based on AFRL's Galaxy Simulation Builder (productivity tool for distributed high performance computing), Sandia Lab's DAKOTA (local and global optimization tool), NRL's CAPSTONE (meshing) [1], and Leidos' MICHELLE (electrostatic particle-in-cell code). The environment leverages high-end parallel computing resources for rapid optimization of complicated problems.

关键词： RF device simulation RF amplifier high-performance computing numerical optimization electron gun depressed electron collector CAPSTONE MICHELLE DAKOTA Galaxy Simulation Builder

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Remote control system for high-perfomance computer simulation of crystal growth by the PFC method

Remote control system for high-perfomance computer simulatio...

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International conference on Structural and Phase Transformations in Materials - Theory, computer Modelling and Experiment (SPTM)

作者： Pavlyuk, Evgeny Starodumov, Ilya Osipov, Sergei Ural Fed Univ Dept Computat Mat & Comp Sci Ekaterinburg 620000 Russia Ural Fed Univ Lab Multiscale Math Modelling Ekaterinburg 620000 Russia Ural Fed Univ Sch Nat Sci & Math Ekaterinburg 620000 Russia

Modeling of crystallization process by the phase field crystal method (PFC) - one of the important directions of modern computational materials science. In this paper, the practical side of the computer simulation of the crystallization process by the PFC method is investigated. To solve problems using this method, it is necessary to use high-performance computing clusters, data storage systems and other often expensive complex computer systems. Access to such resources is often limited, unstable and accompanied by various administrative problems. In addition, the variety of software and settings of different computing clusters sometimes does not allow researchers to use unified program code. There is a need to adapt the program code for each configuration of the computer complex. The practical experience of the authors has shown that the creation of a special control system for computing with the possibility of remote use can greatly simplify the implementation of simulations and increase the performance of scientific research. In current paper we show the principal idea of such a system and justify its efficiency.

关键词： Crystal growth

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Designing a converged plant-wide ethernet/IP lab for hands-on distance learning: An interdisciplinary graduate project 125

Designing a converged plant-wide ethernet/IP lab for hands-o...

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125th ASEE Annual conference and Exposition

作者： Pickard, John Linn, Jimmy Bill Awojana, Tolulope B. Lunsford, Philip J. East Carolina University College of Engineering and Technology United States Technology Systems College of Technology and Computer Science Indiana State University Terre HauteIN United States

Industrial Internet of things (IIoT) is the application of the network of intelligent computers, devices and objects that share huge amounts of data within the manufacturing industry. The days of manually manipulating industrial processes are fading, and quickly being replaced by a complex array of sensors and smart devices that are enabling the fourth industrial revolution through machine-to-machine (M2M) communication and industrial big data analytics. This convergence of information technology (IT) and operations technology (OT) in the IIoT is driving unprecedented levels of efficiency, productivity, and performance. As a result, businesses in power and energy, oil and gas, manufacturing, healthcare, aviation, agriculture, and many other industries are experiencing transformative operational and financial benefits. The implementation of the merging of IT and OT requires skills in both areas, but current programs in colleges and universities typically have the curricula separated. As businesses implement IIoT, the need for workers with combined IT and OT skills has increased. Unfortunately, there is not enough skilled labor to keep pace with the industry's evolution. This IIoT skills gap is one of the greatest challenges manufacturers face. There is a rapidly-growing need for manufacturing employees with certified skills in both IT and OT to design, secure, implement, and maintain these systems. East Carolina University (ECU) endeavors to meet this need through a collaborative workforce development and STEM education network infrastructure to link the university with regional high schools and community colleges designed to prepare a workforce to fill the IIoT skills gap. Central to this education network infrastructure is a remotely accessible Converged Plant-wide Ethernet/IP (CPwE) hands-on lab environment that provides synchronous access to IIoT laboratory experiences. This paper details an interdisciplinary project involving the design, development, and impleme

关键词： Industrial engineering Industrial Internet of Things Industry 4.0 Remote Labs

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Near Real-time performance of Population-based Nature-Inspired Algorithms on Cheaper and Older Smartphones

Near Real-time Performance of Population-based Nature-Inspir...

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International conference on Soft Computing and Machine Intelligence (ISCMI)

作者： Iztok Fister Suash Deb Faculty of Electrical Engineering and Computer Science University of Maribor Maribor Slovenia Decision Sciences and Modeling Program Victoria University Melbourne Australia

ISBN: (纸本)9781728113029

For solving optimization problems, stochastic population-based nature-inspired algorithms use inspirations from nature. Despite their applicability in real-world environments, their bottleneck is high time complexity. Usually, they are searching for optimal solutions on computing devices of full computational power. However, in some situations, we deal with devices of limited computational power. Some examples of such devices are smartphones, which have been becoming very powerful for running various applications. However, there is still a lack of researches that would study the performance of nature-inspired algorithms on these devices. In this paper, we analyze the performance of one member of the nature-inspired algorithms, the so-called Bat algorithm, on the Android smartphone. Although smartphones nowadays offer a computational power comparable with the personal computer, we focus on the cheaper and older smartphones that are most widespread today.

关键词： Smart phones performance evaluation Sociology Statistics Real-time systems Operating systems Benchmark testing

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15th International conference on Parallel Problem Solving from Nature, PPSN 2018

15th International Conference on Parallel Problem Solving fr...

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15th International conference on Parallel Problem Solving from Nature, PPSN 2018

ISBN: (纸本)9783319992525

The proceedings contain 81 papers. The special focus in this conference is on Parallel Problem Solving from Nature. The topics include: Ring migration topology helps bypassing local optima;runtime analysis of evolutionary algorithms for the knapsack problem with favorably correlated weights;theoretical analysis of lexicase selection in multi-objective optimization;towards a running time analysis of the (1+1)-ea for onemax and leadingones under general bit-wise noise;a surrogate model based on walsh decomposition for pseudo-boolean functions;bridging elementary landscapes and a geometric theory of evolutionary algorithms: First steps;empirical analysis of diversity-preserving mechanisms on example landscapes for multimodal optimisation;linear combination of distance measures for surrogate models in genetic programming;on pareto local optimal solutions networks;artificial immune systems can find arbitrarily good approximations for the np-hard partition problem;perturbation strength and the global structure of qap fitness landscapes;sampling local optima networks of large combinatorial search spaces: The qap case;algorithm configuration landscapes: More benign than expected?;a model-based framework for black-box problem comparison using gaussian processes;a suite of computationally expensive shape optimisation problems using computational fluid dynamics;automated selection and configuration of multi-label classification algorithms with grammar-based genetic programming;performance assessment of recursive probability matching for adaptive operator selection in differential evolution;program trace optimization;sampling heuristics for multi-objective dynamic job shop scheduling using island based parallel genetic programming;sensitivity of parameter control mechanisms with respect to their initialization;a simple proof for the usefulness of crossover in black-box optimization;challenges in high-dimensional reinforcement learning with evolution strategies.

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3rd International conference on Industrial Networks and Intelligent Systems, INISCOM 2017

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3rd International conference on Industrial Networksand Intelligent Systems, INISCOM 2017

ISBN: (纸本)9783319741758

The proceedings contain 31 papers. The special focus in this conference is on Industrial Networks and Intelligent Systems. The topics include: Optimization of multi-function sensor placement satisfying detection coverage;toward a real-time development and deployment of IoTs application for smart garden on OpenStack cloud;An energy-aware approach for event-driven multimedia data acquisition in WMSNs;program popularity prediction approach for internet TV based on trend detecting;exact outage probability of two-way decode-and-forward scheme with energy harvesting from intermediate relaying station;enhancing performance of asynchronous cooperative relay network with partial feedback;outage probability for cognitive heterogeneous networks with unreliable backhaul connections;coupling statistical and agent-based models in the optimization of traffic signal control;optimizing vehicle routing with path and carbon dioxide emission for municipal solid waste collection in Ha Giang, Vietnam;energy-efficient data collection using lossless compression for industrial wireless sensor networks;Model-based sensitivity of a disaster tolerant active-active GENESIS cloud system;integrated sentiment and emotion into estimating the similarity among entries on social network;a functional optimization method for continuous domains;Data mining approaches for IP address clustering;a short survey on fault diagnosis of rotating machinery using entropy techniques;An intrusion detection system based on machine learning for CAN-Bus;A buck-boost multilevel inverter for PV systems in smart cities;A new high step-up DC-DC converter for renewable energy applications;method for pseudo-probabilistic block encryption;Crack detection in rotating shafts using wavelet analysis, shannon entropy and multi-class SVM;Outage probability analysis of single energy constraint relay NOMA network.

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15th International conference on Parallel Problem Solving from Nature, PPSN 2018

15th International Conference on Parallel Problem Solving fr...

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15th International conference on Parallel Problem Solving from Nature, PPSN 2018

ISBN: (纸本)9783319992587

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OSPRay - A CPU Ray Tracing Framework for Scientific Visualization

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IEEE TRANSACTIONS ON VISUALIZATION AND computer GRAPHICS 2017年第1期23卷 931-940页

作者： Wald, I. Johnson, G. P. Amstutz, J. Brownlee, C. Knoll, A. Jeffers, J. Guenther, J. Navratil, P. Intel Corp Santa Clara CA 95051 USA Texas Adv Comp Ctr Austin TX USA Univ Utah SCI Inst Salt Lake City UT 84112 USA Argonne Natl Lab 9700 S Cass Ave Argonne IL 60439 USA

Scientific data is continually increasing in complexity, variety and size, making efficient visualization and specifically rendering an ongoing challenge. Traditional rasterization-based visualization approaches encounter performance and quality limitations, particularly in HPC environments without dedicated rendering hardware. In this paper, we present OSPRay, a turn-key CPU ray tracing framework oriented towards production-use scientific visualization which can utilize varying SIMD widths and multiple device backends found across diverse HPC resources. This framework provides a high-quality, efficient CPU-based solution for typical visualization workloads, which has already been integrated into several prevalent visualization packages. We show that this system delivers the performance, high-level API simplicity, and modular device support needed to provide a compelling new rendering framework for implementing efficient scientific visualization workflows.

关键词： Data visualization Rendering (computer graphics) Ray tracing Pipelines Data models Computational modeling Graphics processing units

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