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8th International Conference on Optimization and Applications, OPTIMA 2017

作者： Afanasiev, Alexander P. Krivonozhko, Vladimir E. Lychev, Andrey V. Sukhoroslov, Oleg V. Centre for Distributed Computing Institute for Information Transmission Problems Russian Academy of Sciences Nakhimovsky Prospekt 36-1 Moscow117218 Russia National University of Science and Technology MISiS Leninskiy Prospekt 4 Moscow119049 Russia Lomonosov Moscow State University GSP-1 Vorobievy Gory Moscow119991 Russia National Research University Higher School of Economics Myasnitskaya str. 20 Moscow101000 Russia Federal Research Center Computer Science and Control Russian Academy of Sciences Vavilov st. 44-2 Moscow119333 Russia

In data envelopment analysis, methods for constructing sections of the frontier have been recently proposed to visualize the production possibility set. The aim of this paper is to develop, prove and test the methods for the visualization of production possibility sets using distributed computations. In this article a general scheme of the algorithm for constructing sections (visualization) of production possibility set is proposed. An algorithm for constructing a generalized production function is described in detail. Also, the possibilities of implementing certain schemes in a distributed computing environment are considered. © Copyright by the paper's authors.

关键词： Visualization

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Cloning agent-based simulation on GPU 15

Cloning agent-based simulation on GPU

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3rd ACM Conference on SIGSIM-Principles of Advanced Discrete Simulation, SIGSIM-PADS 2015

作者： Li, Xiaosong Cai, Wentong Turner, Stephen John Parallel and Distributed Computing Center School of Computer Engineering Nanyang Technological University Singapore Singapore

ISBN: (纸本)9781450335836

Simulation cloning is an efficient way to analyze multiple configurations in a parameter exploration task. This paper presents a generic approach to perform incremental agentbased simulation cloning and discusses its implementation on GPU. Compared with the incremental cloning of parallel and distributed simulation (PADS), cloning agent-based simulation (ABS) has new challenges due to the unique way how ABS is executed. In this paper, to support incremental cloning, mechanisms for both actively and passively cloning agents are proposed. A scheme to maintain the correct context of each cloned ABS instance is developed. In addition, a strategy to restrain the propagation of passive cloning in order to maximize computation sharing amongst cloned ABS instances is also investigated. The implementation of our proposed approach on GPU supports concurrent execution of agents within each simulation instance as well as concurrent execution of multiple simulation instances. Performance of the proposed approach is evaluated and analyzed using a case study of an agent-based evacuation simulation on a NVIDIA Quadro 2000 GPU. Our experiment results demonstrate that cloning can significantly speed up the overall parameter exploration task. The proposed approach achieves 2.4 to 5.1 times speedup for parameter exploration tasks containing 8 to 125 simulation instances that evaluate different parameter configurations. © 2015 ACM.

关键词： speedup agent-based simulation gpu cloning

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From event labeled gene trees to species trees

arXiv

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arXiv 2017年

作者： Hernandez-Rosales, Maribel Hellmuth, Marc Wieseke, Nicolas Huber, Katharina T. Moulton, Vincent Stadler, Peter F. Dpt. of Mathematics and Computer Science University of Greifswald Walther- Rathenau-Strasse 47 GreifswaldD-17487 Saarland University Center for Bioinformatics Building e 2.1 P.O. Box 151150 SaarbrückenD-66041 Bioinformatics Group Department of Computer Science Interdisciplinary Center of Bioinformatics University of Leipzig Härtelstraße 16-18 LeipzigD-04107 Germany School of Computing Sciences University of East Anglia NorwichNR4 7TJ United Kingdom Max-Planck-Institute for Mathematics in the Sciences Inselstraße 22 LeipzigD-04103 Germany Inst. F. Theoretical Chemistry University of Vienna Währingerstraße 17 WienA-1090 Austria Santa Fe Institute 1399 Hyde Park Rd. Santa Fe United States Parallel Computing and Complex Systems Group Department of Computer Science Leipzig University Augustusplatz 10 Leipzig04109 Germany

Background: Tree reconciliation problems have long been studied in phylogenetics. A particular variant of the reconciliation problem for a gene tree T and a species tree S assumes that for each interior vertex x of T it is known whether x represents a speciation or a duplication. This problem appears in the context of analyzing orthology data. Results: We show that S is a species tree for T if and only if S displays all rooted triples of T that have three distinct species as their leaves and are rooted in a speciation vertex. A valid reconciliation map can then be found in polynomial time. Simulated data shows that the event-labeled gene trees convey a large amount of information on underlying species trees, even for a large percentage of losses. Conclusions: The knowledge of event labels in a gene tree strongly constrains the possible species tree and, for a given species tree, also the possible reconciliation maps. Nevertheless, many degrees of freedom remain in the space of feasible solutions. In order to disambiguate the alternative solutions additional external constraints as well as optimization criteria could be employed. Copyright © 2017, The Authors. All rights reserved.

关键词： Polynomial approximation

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Preface

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International Journal of High Performance computing and Networking 2017年第1-2期10卷 1-2页

作者： Vijayakumar, V. Anderst-Kotsis, Gabriele Cai, Zhipeng Abawajy, Jemal H. School of Computing Science and Engineering VIT University Chennai600127 India Department of Telecooperation Johannes Kepler Universität AltenbergerStrasse 69 Linz4040 Austria Department of Computer Science Georgia State University AtlantaGA30303 United States Parallel and Distributed Computing Lab. Deakin University GeelongVIC3220 Australia

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Accelerating FDTD simulation of microwave pulse coupling into narrow slots on the Intel MIC architecture

Accelerating FDTD simulation of microwave pulse coupling int...

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IEEE Pacific Rim Conference on Communications, computers and Signal Processing, PACRIM 2015

作者： Wang, Qinglin Liu, Jie Cui, Xiantao Fu, Guitao Gong, Chunye Xing, Zuocheng Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha410073 China School of Computer Science National University of Defense Technology Changsha410073 China Beijing Satellite Navigation Center Beijing100094 China

ISBN: (纸本)9781467377881

The coupling of microwaves into apertures plays an important part in many electromagnetic physics and engineering fields. When the width of apertures is very small, Finite Difference Time Domain (FDTD) simulation of the coupling is very time-consuming. As a many-core architecture, the Intel's Many Integrated Core (MIC) architecture owns 512-bit vector units and more than 200 threads. In this paper, we parallelize FDTD simulation of microwave pulse coupling into narrow slots on the Intel MIC architecture. In the implementation, the parallel programming model OpenMP is used to exploit thread parallelism while loop unrolling and SIMD intrinsic functions are utilized to accomplish vectorization. Compared with the serial version on Intel Xeon E5-2670 CPU, the implementation on the MIC coprocessor including 57 cores obtains a speedup of 11.57 times. The experiment results also demonstrate that the parallelization has good scalability in performance. Additionally, how binding relationship between OpenMP threads and hardware threads in MIC influences performance is also reported. © 2015 IEEE.

关键词： Scalability

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Madness: A multiresolution, adaptive numerical environment for scientific simulation

Madness: A multiresolution, adaptive numerical environment f...

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作者： Harrison, Robert J. Beylkin, Gregory Bischoff, Florian A. Calvin, Justus A. Fann, George I. Fosso-Tande, Jacob Galindo, Diego Hammond, Jeff R. Hartman-Baker, Rebecca Hill, Judith C. Jia, Jun Kottmann, Jakob S. Ou, M-J. Yvonne Pei, Junchen Ratcliff, Laura E. Reuter, Matthew G. Richie-Halford, Adam C. Romero, Nichols A. Sekino, Hideo Shelton, William A. Sundahl, Bryan E. Thornton, W. Scott Valeev, Edward F. Vázquez-Mayagoitia, Álvaro Vence, Nicholas Yanai, Takeshi Yokoi, Yukina Stony Brook University Stony BrookNY11794 United States University of Colorado at Boulder BoulderCO80309 United States Institut für Chemie Humboldt-Universität Zu Berlin Unter den Linden 6 Berlin10099 Germany Department of Chemistry Virginia Tech. BlacksburgVA24061 United States Oak Ridge National Laboratory Oak RidgeTN37831 United States Department of Chemistry and Biochemistry Florida State University TallahasseeFL32306 United States Parallel Computing Lab Intel Corporation PortlandOR97219 United States National Energy Research Scientific Computing Center Lawrence Berkeley National Laboratory BerkeleyCA94720 United States LinkedIn Mountain ViewCA94043 United States Department of Mathematical Sciences University of Delaware NewarkDE19716 United States State Key Laboratory of Nuclear Physics and Technology School of Physics Peking University Beijing100871 China Argonne Leadership Computing Facility Argonne National Laboratory ArgonneIL60439 United States Department of Physics University of Washington SeattleWA98195 United States Computer Science and Engineering Toyohashi University of Technology ToyohashiAichi441-8580 Japan Louisiana State University Baton RougeLA70803 United States Department of Physics LaSierra University RiversideCA92505 United States Theoretical and Computational Molecular Science Institute for Molecular Science OkazakiAichi444-8585 Japan

MADNESS (multiresolution adaptive numerical environment for scientific simulation) is a high-level software environment for solving integral and differential equations in many dimensions that uses adaptive and fast harmonic analysis methods with guaranteed precision that are based on multiresolution analysis and separated representations. Underpinning the numerical capabilities is a powerful petascale parallel programming environment that aims to increase both programmer productivity and code scalability. This paper describes the features and capabilities of MADNESS and briefly discusses some current applications in chemistry and several areas of physics. © 2016 Society for Industrial and Applied Mathematics.

关键词： Multiresolution analysis

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Accelerating FDTD simulation of microwave pulse coupling into narrow slots on the Intel MIC architecture

Accelerating FDTD simulation of microwave pulse coupling int...

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IEEE Pacific Rim Conference on Communications, computers and Signal Processing

作者： Qinglin Wang Jie Liu Xiantao Cui Guitao Fu Chunye Gong Zuocheng Xing School of Computer Science National University of Defense Technology Changsha China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China Beijing Satellite Navigation Center Beijing China

ISBN: (纸本)9781467377898

关键词： Microwave integrated circuits Finite difference methods Time-domain analysis Chlorine Hardware

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Location-Aware Multi-user Resource Allocation in distributed Clouds

Location-Aware Multi-user Resource Allocation in Distributed...

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10th Annual Conference of Advanced computer Architecture, ACA 2014

作者： Li, Jiaxin Li, Dongsheng Zheng, Jing Quan, Yong National Key Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China Information Center of Logistics Department Beijing China School of Computer Science National University of Defense Technology Changsha China

ISBN: (纸本)9783662444900

Resource allocation for multi-user across multiple data centers is an important problem in cloud computing environments. Many geographically-distributed users may request virtualized resources simultaneously. And the distances from users to allocated resources have much impact on the quality of service (QoS) in multiple data centers environment. Most existing methods do not take all these factors into account when allocating resources. They usually result in poor runtime performance of users' virtual computing environment and the remarkable difference of users' QoS. In this paper, we propose RAMD, a resource allocation algorithm based on multi-stage decision in multiple data centers. The RAMD algorithm allocate VMs to users, taking into account the correlation and interaction between multiple users, so as to minimize the sum of all users' service distances (i.e. determined by user location and network distance of virtual machines). Experimental results show that the algorithm can effectively deal with the cloud resource allocation for multi-user across multiple data centers. It can improve the runtime performance of users' virtualized resources and reduce the difference of QoS. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Resource allocation

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RAFlow: Read Ahead Accelerated I/O Flow through Multiple Virtual Layers

RAFlow: Read Ahead Accelerated I/O Flow through Multiple Vir...

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International Conference on Networking, Architecture, and Storage (NAS)

作者： Zhaoning Zhang Kui Wu Huiba Li Jinghua Feng Yuxing Peng Xicheng Lu National Key Laboratory for Parallel and Distributed Processing National University of Defense Technology China Computer Science Department University of Victoria B.C. Canada National Super Computing Center Tianjin China

Virtualization is the foundation for cloud computing, and the virtualization can not be achieved without software defined, elastic, flexible and scalable virtual layers. Unfortunately, if multiple virtual storage devices are chained together, the system may be subject to severe performance degradation. While the read-ahead (RA) mechanism in storage devices plays a very important role to improve I/O performance, RA may not be effective as expected for multiple virtualization layers, since it is originally designed for one layer only. When I/O requests are passed through a long I/O path, they may trigger a chain reaction and lead to unnecessary data transmission and thus bandwidth waste. In this paper, we study the dynamic behavior of RA through multiple I/O layers and demonstrate that if controlled well, RA can greatly accelerate I/O speed. We present RAFlow, a RA control mechanism, to effectively improve I/O performance by strategically expanding RA window at each layer. Our real-world experiments show that it can achieve 20% to 50% performance improvement in I/O paths with up to 8 virtualized storage devices.

关键词： Radio access networks Acceleration distributed databases Performance evaluation Synchronization Benchmark testing Degradation

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GPU accelerated three-stage execution model for event-parallel simulation 13

GPU accelerated three-stage execution model for event-parall...

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2013 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation, SIGSIM-PADS 2013

作者： Li, Xiaosong Cai, Wentong Turner, Stephen John Parallel and Distributed Computing Center School of Computer Engineering Nanyang Technological University Singapore 639798 Singapore

ISBN: (纸本)9781450319201

This paper introduces the concept of event-parallel discrete event simulation (DES) and its corresponding implementation on the GPU platform. Inspired by the typical spatial-parallel DES and time-parallel DES, the event-parallel approach on GPU uses each thread to process one of the N events, where N is the total number of events. By taking advantage of the high parallelism of GPU threads, this approach achieves greater speedup. The GPU architecture is adopted in the execution of the event-parallel approach, so as to take advantage of the parallel processing capability provided by the massively large number of GPU threads. A three-stage execution model composing of generating events, sorting events and processing events in parallel is proposed. This execution model achieves good speedup. Compared with the event scheduling approach on CPU, we achieve up to 22.80 speedup in our case study. © 2013 ACM.

关键词： Graphics processing unit

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