Search Results - parallel computing ((graph algorithm) OR (path algorithm))*

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    High-Speed shortest path co-processor design by Idris, Mohd Yamani Idna, Abu Bakar, Suraya, Tamil, Emran Mohd, Razak, Zaidi, Noor, Noorzaily Mohamed

    Published 2009
    “…Shortest path algorithms are significant in graph theory and have been applied in many applications such as transportation and networking. …”
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    Unconstraint assignment problem : a molecular computing approach by Zuwairie, Ibrahim, Yusei, Tsuboi, Osamu, Ono, Marzuki, Khalid

    Published 2006
    “…Since DNA computing is very suitable for combinatorial problems, in thispaper, an idea on DNA-based computing algorithm for solving unconstraint assignment problem is proposed. …”
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    Communication in Chordal Ring Networks by Matroud, Atheer Abbas

    Published 2006
    “…Based on the existing results in [61] done by Narayanan and Opatrny, we propose a new algorithm for some families of chordal ring of degree six graphs. …”
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    Solving traveling salesman problem on cluster compute nodes by I.A., Aziz, Haron, N., Mehat, M., Jung, L.T., Mustapa, A.N., Akir, E.A.P.

    Published 2009
    “…The sequential algorithm is then converted into a parallel algorithm by integrating it with the Message Passing Interface (MPI) libraries so that it can be executed on a cluster computer. …”
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    Tool path generation of contour parallel based on ant colony optimisation by Abdullah, Haslina, Ramli, Rizauddin, Abd Wahab, Dzuraidah, Abu Qudeiri, Jaber

    Published 2016
    “…The optimisation of tool path length based on ACO algorithm ascertained that the cutting tool remove the uncut line once and able to eliminate the uncut region in the shortest tool path length. …”
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    A genetic similarity algorithm for searching the Gene Ontology terms and annotating anonymous protein sequences by M. Othman, Razib, Deris, Safaai, Md. IIlias, Rosli

    Published 2008
    “…The genetic similarity algorithm combines semantic similarity measure algorithm with parallel genetic algorithm. …”
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    Generic DNA encoding design scheme to solve combinatorial problems by Rofilde, Hasudungan

    Published 2015
    “…However, DNA computing can solve the problem in linear time since the parallel processing power of DNA computing is able to generate a solution in a single process. …”
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    Random sampling method of large-scale graph data classification by Rashed Mustafa, Mohammad Sultan Mahmud, Mahir Shadid

    Published 2024
    “…After that, we randomly select a subset of data blocks, each being a random sample of the graph dataset, and compute the different graph property distributions. …”
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  12. 12

    DNA Computing Technique to Solve Vertex Coloring Problem by Hasudungan, Rofilde, Rohani, Abu Bakar

    Published 2013
    “…In this paper we proposed DNA based computer to solve vertex coloring problem where in this paper we proposed DNA encoding and computational procedure inspired by greedy algorithm to generate all possible solutions to coloring a graph.…”
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    Partitioning techniques and their parallelization for stiff system of ordinary differential equations by Othman, Khairil Iskandar

    Published 2007
    “…The graphs of its performance and execution time, visualize the advantages of parallelizing.…”
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    A new parameterized architectural design for SENSE reconstruction by Siddiqui, M.F., Reza, A.W., Kanesan, J., Omer, H.

    Published 2014
    “…Reconfigurable hardware based architectures that could provide good quality image reconstruction for parallel Magnetic Resonance Imaging (MRI) within very less computation time are in high demand. …”
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    A novel large-bit-size architecture and microarchitecture for the implementation of Superscalar Pipeline VLIW microprocessors by Lee, Weng Fook

    Published 2008
    “…To further grow the computational capability of a microprocessor, there are two possible paths. …”
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    Hybrid Method for Digits Recognition using Fixed-Frame Scores and Derived Pitch by Sudirman, Rubita, Salleh, Sh-Hussain, Salleh, Shaharuddin

    Published 2006
    “…The enthusiasm to this study is due to neural network limitation that entails a fix number of input nodes for when processing multiple inputs in parallel. Due to this problem, this research is initiated to reduce the amount of computation and complexity in a neural network by reducing the number of inputs into the network. …”
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