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parallel algorithm for setting WIP levels for multi-product CONWIP systems

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2006年第21期44卷 4681-4693页

作者： Wang, L. Prabhu, V. Harold & Inge Marcus Dept Ind & Mfg Engn University Pk PA 16802 USA

Reducing work-in-process (WIP) inventory is continuing to be an important business need because of several factors including the need to reduce working capital. Numerous techniques have been suggested for WIP reduction, and CONWIP is a competitive algorithm for WIP reduction. Prior CONWIP algorithms have been primarily sequential algorithms and can be potentially incur significant computing time, especially when dealing with inventories for multiple products. The paper proposes a card-setting algorithm for multiple product types subject to routing and throughput requirements. The proposed algorithm searches the WIP space iteratively and the step-size is adaptively selected based on the known properties of multi-chain, multi-class, closed queuing networks. Furthermore, parallelization of this search algorithm across multiple processors is proposed where each processor searches a different segment of the WIP space while adaptively adjusting its step size for all product types to ensure fast convergence. The proposed parallel algorithm can take advantage of distributed computing architectures to speed-up the overall computation. An experimental implementation of the parallel algorithm using Message Passing Interface (MPI) over a high-speed network is described. Computational results demonstrate that the proposed parallel algorithm can be parallelized over eight to ten processors to obtain a speed-up of three to five.

关键词： multi-product CONWIP systems parallel algorithm distributed computer memory system Message Passing Interface (MPI) speed-up

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An efficient parallel algorithm for finding the (k, l)-center of tree networks

An efficient parallel algorithm for finding the (<i>k</i>, <...

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18th IASTED International Conference on parallel and Distributed Computing and Systems

作者： Wang, Deqiang Li, Yuanhui Wang, Yan Wang, Kelun Dalian Maritime Univ Naut Sci & Technol Inst Dalian 116026 Peoples R China Northwest A & F Univ Sci Dept Yangling 712100 Peoples R China Dalian Maritime Univ Dept Math Dalian 116026 Peoples R China

ISBN: (纸本)9780889866386

This paper research on how to select a subtree with exactly k leaves and a diameter of at most 1, which minimizes the distance from the farthest vertex to the subtree. We call such a subtree (k, l)-center of a tree network. In this paper, an efficient parallel algorithm is proposed for finding a (k, l)-center of a tree network. This algorithm performs on the EREW PRAM in O(log n) time using O(n) work.

关键词： tree center parallel algorithm EREW PRAM

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SCALABLE HEURISTIC algorithmS FOR THE parallel EXECUTION OF DATA FLOW ACYCLIC DIGRAPHS

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SIAM JOURNAL ON SCIENTIFIC COMPUTING 2009年第5期31卷 3626-3642页

作者： Mo, Zeyao Zhang, Aiqing Wittum, Gabriel Inst Appl Phys & Computat Math Lab Computat Phys Beijing 100088 Peoples R China Heidelberg Univ IWR Tech Simulat Grp D-69120 Heidelberg Germany Goethe Univ Frankfurt Goethe Ctr Sci Comp D-60325 Frankfurt Germany

Data flow acyclic directed graphs (digraphs) can be applied to accurately describe the data dependency for a wide range of grid-based scientific computing applications ranging from numerical algebra to realistic applications of radiation or neutron transport. The parallel computing of these applications is equivalent to the parallel execution of digraphs. This paper presents a framework of scalable heuristic algorithms for the parallel execution of digraphs. This framework consists of three components: the heuristic partitioning method of a digraph, the parallel sweeping algorithm for a partitioned digraph, and the heuristic strategy for vertex scheduling and vertex packing. Evaluation rules of heuristic algorithms are presented for better theoretical understanding and performance optimization. parallel benchmarks for the multigroup neutron or radiation S-n transport using processors from 100 to 2048 on two massively parallel machines show that these heuristic algorithms scale well.

关键词： parallel algorithm acyclic digraph grid-based scientific computing Sn transport

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On some new approximate factorization methods for block tridiagonal matrices suitable for vector and parallel processors

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MATHEMATICS AND COMPUTERS IN SIMULATION 2009年第7期79卷 2135-2147页

作者： Li, Hou-Biao Huang, Ting-Zhu Zhang, Yong Liu, Xing-Ping Li, Hong Univ Elect Sci & Technol China Sch Appl Math Chengdu 610054 Sichuan Peoples R China Inst Appl Phys & Computat Math Lab Comp Phy Beijing 100088 Peoples R China

In this paper, to obtain an efficient parallel algorithm to solve sparse block-tridiagonal linear systems, stair matrices are used to construct some parallel polynomial approximate inverse preconditioners. These preconditioners are suitable when the desired goal is to maximize parallelism. Moreover, some theoretical results concerning these preconditioners are presented and how to construct preconditioners effectively for any nonsingular block tridiagonal H-matrices is also described. In addition, the validity of these preconditioners is illustrated with some numerical experiments arising from the second order elliptic partial differential equations and oil reservoir Simulations. (C) 2008 IMACS. Published by Elsevier B.V. All rights reserved.

关键词： Tridiagonal matrix Stair matrix Polynomial sparse approximate Preconditioning parallel algorithm

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Solving the flow shop problem by parallel programming

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JOURNAL OF parallel AND DISTRIBUTED COMPUTING 2009年第5期69卷 470-481页

作者： Bozejko, Wojciech Wroclaw Univ Technol Inst Comp Engn Control & Robot PL-50372 Wroclaw Poland

The matter of using scheduling algorithms in parallel computing environments is discussed in this paper. There are proposed methods of parallelizing the criterion function calculations for a single solution and a group of concentrated solutions (local neighborhood) dedicated to being used in metaheuristic approaches. Also a parallel scatter-search metaheuristic is proposed as a multiple-thread approach. Computational experiments are done for the flow shop, the classic NP-hard problem of the combinatorial optimization. (C) 2009 Elsevier Inc. All rights reserved.

关键词： parallel algorithm Flow shop problem PRAM

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A new parallel algorithm of MP2 energy calculations

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JOURNAL OF COMPUTATIONAL CHEMISTRY 2006年第4期27卷 407-413页

作者： Ishimura, K Pulay, P Nagase, S Inst Mol Sci Dept Theoret Mol Sci Okazaki Aichi 4448585 Japan Univ Arkansas Dept Chem & Biochem Fayetteville AR 72701 USA

A new parallel algorithm has been developed for second-order Moller-Plesset perturbation theory (MP2) energy calculations. Its main projected applications are for large molecules, for instance, for the calculation of dispersion interaction. Tests on a moderate number of processors (2-16) show that the program has high CPU and parallel efficiency. Timings are presented for two relatively large molecules, taxol (C47H51NO14) and luciferin (C11H8N2O3S2), the former with the 6-31G* and 6-311G** basis sets (1032 and 1484 basis functions, 164 correlated orbitals), and the latter with the aug-cc-pVDZ and aug-cc-pVTZ basis sets (530 and 1198 basis functions, 46 correlated orbitals). An MP2 energy calculation on C130H10 (1970 basis functions, 265 con-elated orbitals) completed in less than 2 h on 128 processors. (c) 2006 Wiley Periodicals, Inc.

关键词： MP2 energy parallel algorithm large molecule

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An efficient parallel sorting compatible with the standard qsort

An efficient parallel sorting compatible with the standard q...

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10th International Conference on parallel and Distributed Computing, Applications and Technologies

作者： Man, Duhu Ito, Yasuaki Nakano, Koji Hiroshima Univ Dept Informat Engn Hiroshima 7398527 Japan

ISBN: (纸本)9781424452910

The main contribution of this paper is to present an efficient parallel sorting "psort" compatible with the standard qsort. Our parallel sorting "psort" is implemented such that its interface is compatible with "qsort" in C Standard Library. Therefore, any application program that uses standard "qsort" can be accelerated by simply replacing "qsort" call by our "psort". Also, "psort" uses standard "qsort" as a "subroutine for local sequential sorting. So, if the performance of "qsort" is improved by anyone in the community, then that of our "psort" is also automatically improved. To evaluate the performance of our "psort", we have implemented our parallel sorting in a Linux server with two Intel quad-core processors (i.e. eight processor cores). The experimental results show that our "psort" is approximately 6 times faster than standard "qsort" using 8 processors. Since the speed up factor cannot be more than 8 if we use 8 cores, our algorithm is close to optimal. Also, as far as we know, no previously published parallel implementations achieve a speed up factor less than 4 using 8 cores.

关键词： parallel algorithm Sorting Multicore processor C standard library

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Mean Shift parallel Tracking on GPU

Mean Shift Parallel Tracking on GPU

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4th Iberian Conference on Pattern Recognition and Image Analysis

作者： Li, Peihua Xiao, Lijuan Heilongjiang Univ Sch Comp Sci & Technol Harbin 150080 Heilongjiang Pr Peoples R China

ISBN: (纸本)9783642021718

We propose a parallel Mean Shift (MS) tracking algorithm on Graphics Processing Unit (GPU) using Compute Unified Device Architecture (CUDA). Traditional MS algorithm uses a large number of color histogram, say typically 16x16x16, which makes parallel implementation infeasible. We thus employ K-Means clustering to partition the object color space that enables us to represent color distribution with a quite small number of bins. Based on this compact histogram, all key components of the MS algorithm are mapped onto the GPU. The resultant parallel algorithm consist of six kernel functions, which involves primarily the parallel computation of the candidate histogram and calculation of the Mean Shift vector. Experiments on public available CAVIAR videos show that the proposed parallel tracking algorithm achieves large speedup and has comparable tracking performance, compared with the traditional serial MS tracking algorithm.

关键词： Mean Shift tracking parallel algorithm GPU CUDA

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Numerical parallel Processing Based on GPU with CUDA Architecture

Numerical Parallel Processing Based on GPU with CUDA Archite...

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International Conference on Wireless Networks and Information Systems

作者： Zou, Chengming Xia, Chunfen Zhao, Guanghui Wuhan Univ Technol Coll Comp Sci & Technol Wuhan 430070 Peoples R China

ISBN: (纸本)9780769539010

The characteristics of modern graphics processing unit (GPU) is programmable, high price / performance ratio and high speed. It has a strong ability to adapt the parallel calculation, Based on this, the article study the general method of GPU calculating and use compute unified device architecture (CUDA) to design new parallel algorithm to accelerate the matrix inversion and Binarization algorithm. The results show that with the increase of matrix dimension, CPU performs much better than CPU in increase multiple.

关键词： GPU parallel algorithm CUDA matrix inversion Binarization algorithm

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parallel Community Detection on Large Networks with Propinquity Dynamics 09

Parallel Community Detection on Large Networks with Propinqu...

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15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

作者： Zhang, Yuzhou Wang, Jianyong Wang, Yi Zhou, Lizhu Tsinghua Univ Dept Comp Sci & Technol Beijing 100084 Peoples R China

ISBN: (纸本)9781605584959

Graphs or networks can be used to model complex systems. Detecting community structures from large network data is a classic and challenging task. In this paper, we propose a novel community detection algorithm, which utilizes a dynamic process by contradicting the network topology and the topology-based propinquity, where the propinquity. is a measure of the probability for a pair of nodes involved in a coherent community structure. Through several rounds of mutual reinforcement between topology and propinquity, the community structures are expected to naturally emerge. The overlapping vertices shared between communities can also be easily identified by an additional simple post-processing. To achieve better efficiency, the propinquity is incrementally calculated. We implement the algorithm on a vertex-oriented bulk synchronous parallel(BSP) model so that the mining load can be distributed on thousands of machines. We obtained interesting experimental results on several real network data.

关键词： data mining community detection parallel algorithm bulk synchronous parallel graph mining

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