Výsledky vyhľadávania - (( key yorks parallel/distributed algorithms ) OR ( key work parallel/distributed algorithms ))~

  1. 1

    A Latency-Hiding Algorithm for ABMS on Parallel/Distributed Computing Environment Autor Li-li Chen, Jian-xin Huang, Jing Zhang

    ISBN: 9781467317979, 1467317977
    ISSN: 1087-4097
    Vydavateľské údaje: IEEE 01.07.2012
    “…) on parallel/distributed computing platform is proposed. The key idea of this algorithm is using redundant computations to hide communication latencies…”
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  2. 2

    Fast and Precise: Parallel Processing of Vehicle Traffic Videos Using Big Data Analytics Autor Perafan-Villota, Juan C., Mondragon, Oscar H., Mayor-Toro, Walter M.

    ISSN: 1524-9050, 1558-0016
    Vydavateľské údaje: New York IEEE 01.08.2022
    “… Computer vision can be used in combination with parallel distributed systems to provide city authorities tools for automatic and fast processing of stored videos to determine the most significant…”
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  3. 3

    Exploiting Simultaneous Communications to Accelerate Data Parallel Distributed Deep Learning Autor Shi, Shaohuai, Chu, Xiaowen, Li, Bo

    ISSN: 2641-9874
    Vydavateľské údaje: IEEE 10.05.2021
    “…) is a key ingredient to improve communication efficiency. However, existing tensor fusion techniques schedule the communication tasks sequentially, which overlooks their independence nature…”
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  4. 4

    A parallel, distributed memory implementation of the adaptive sampling configuration interaction method Autor Williams-Young, David B, Tubman, Norm M, Mejuto-Zaera, Carlos, de Jong, Wibe A

    ISSN: 1089-7690, 1089-7690
    Vydavateľské údaje: United States 07.06.2023
    Vydané v The Journal of chemical physics (07.06.2023)
    “… Here, we present a parallel, distributed memory implementation of the adaptive sampling configuration interaction approach (ASCI) for sCI…”
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  5. 5

    Using parallel & distributed computing for real-time solving of vehicle routing problems with stochastic demands Autor Juan, Angel A., Faulin, Javier, Jorba, Josep, Caceres, Jose, Marquès, Joan Manuel

    ISSN: 0254-5330, 1572-9338
    Vydavateľské údaje: Boston Springer US 01.08.2013
    Vydané v Annals of operations research (01.08.2013)
    “… Thus, for a given VRPSD instance, our algorithm considers different levels of safety stocks…”
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  6. 6

    Scalable distributed data cube computation for large-scale multidimensional data analysis on a Spark cluster Autor Lee, Suan, Kang, Seok, Kim, Jinho, Yu, Eun Jung

    ISSN: 1386-7857, 1573-7543
    Vydavateľské údaje: New York Springer US 01.01.2019
    Vydané v Cluster computing (01.01.2019)
    “… Previous works have developed various algorithms for efficiently generating data cubes using MapReduce, which is a large-scale distributed parallel processing framework…”
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  7. 7

    Efficient Anytime Anywhere Algorithms for Closeness Centrality in Large and Dynamic Graphs Autor Santos, Eunice E., Korah, John, Murugappan, Vairavan, Subramanian, Suresh

    Vydavateľské údaje: IEEE 01.05.2016
    “… In our previous work, we presented an overarching anytime anywhere framework for designing parallel and distributed social network analysis algorithms that are scalable to large network sizes and can handle dynamism…”
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  8. 8

    Takagi–Sugeno fuzzy-based approach for modeling and control of an activated sludge process Autor Arifi, Ali, Bouallègue, Soufiene

    ISSN: 2195-268X, 2195-2698
    Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2024
    “… Given its better performance, biological treatment via an activated sludge process (ASP) represents the key phase in the overall treatment chain…”
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  9. 9

    An efficient theta-join query processing in distributed environment Autor Liu, Wenjie, Li, Zhanhuai

    ISSN: 0743-7315, 1096-0848
    Vydavateľské údaje: Elsevier Inc 01.11.2018
    “… In this work, we propose a filter method for theta-join on the purpose of reducing the computation cost and achieving the minimum execution time in distributed environment…”
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    Influence of the Migration Policy in Parallel Distributed GAs with Structured and Panmictic Populations Autor Alba, Enrique, Troya, José M.

    ISSN: 0924-669X, 1573-7497
    Vydavateľské údaje: Boston Springer Nature B.V 01.05.2000
    “… The difference lies in whether any individual in the population can mate with any other one or not. In this work, they are both considered as two reproductive loop types executed in the islands of a parallel distributed GA…”
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    Optimizing Machine Learning Algorithms on Multi-Core and Many-Core Architectures Using Thread and Data Mapping Autor Serpa, Matheus S., Krause, Arthur M., Cruz, Eduardo H.M., Navaux, Philippe Olivier Alexandre, Pasin, Marcelo, Felber, Pascal

    ISSN: 2377-5750
    Vydavateľské údaje: IEEE 01.03.2018
    “… The algorithms at the core of machine learning are notoriously demanding in terms of resources…”
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    An Automated Staff Roster Planning System (SRPS) For Healthcare Industry Autor Zhu, Larry Ruohua, Tong, Jun Hong, Low, Malcolm Yoke Hean, Lau, Ben Hsin, Chen, Mary Xiaorong, Wang, Zhengkui

    Vydavateľské údaje: IEEE 01.07.2019
    “…This paper proposed an automated staff roster planning system (SRPS) for the healthcare sector with the objective to revolutionize the existing approach of…”
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  13. 13

    Parallel distributed numerical simulations in aeronautic applications Autor Alléon, G., Champagneux, S., Chevalier, G., Giraud, L., Sylvand, G.

    ISSN: 0307-904X
    Vydavateľské údaje: Elsevier Inc 01.08.2006
    Vydané v Applied mathematical modelling (01.08.2006)
    “…The numerical simulation plays a key role in industrial design because it enables to reduce the time and the cost to develop new products…”
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  14. 14

    Dynamic Application Mapping Algorithm for Wireless Network-on-Chip Autor Rezaei, Amin, Daneshtalab, Masoud, Zhao, Danella, Safaei, Farshad, Xiaohang Wang, Ebrahimi, Masoumeh

    ISSN: 1066-6192
    Vydavateľské údaje: IEEE 01.01.2015
    “… However, congestion occurrence in wireless routers reduces the benefit of high speed wireless links and significantly increases the network latency, therefore, in this paper, a Dynamic Application Mapping Algorithm (DAMA…”
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    Parallel Branch-and-Bound in multi-core multi-CPU multi-GPU heterogeneous environments Autor Vu, Trong-Tuan, Derbel, Bilel

    ISSN: 0167-739X, 1872-7115
    Vydavateľské údaje: Elsevier B.V 01.03.2016
    Vydané v Future generation computer systems (01.03.2016)
    “… B&B algorithms while describing efficient techniques…”
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    GPU Implementation of Inverse Iteration Algorithm for Computing Eigenvectors Autor Ishigami, Hiroyuki, Kimura, Kinji, Nakamura, Yoshimasa

    ISSN: 1066-6192
    Vydavateľské údaje: IEEE 01.02.2014
    “… The key to effectively accelerating the inverse iteration algorithm in GPU computing is the adoption of reorthogonalization code optimal for the GPU…”
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    Enhancing the Scalability and Memory Usage of Hashsieve on Multi-core CPUs Autor Mariano, Artur, Bischof, Christian

    ISSN: 2377-5750
    Vydavateľské údaje: IEEE 01.02.2016
    “… This is a problem because the asymptotic complexity of the best algorithms plays a key role in the construction of cryptosystems, but only practically appealing, validated algorithms are accounted for in this…”
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    XORAdap: A HoL-Blocking Aware Adaptive Routing Algorithm Autor Penaranda, Roberto, Gomez, Crispin, Gomez, Maria Engracia, Lopez, Pedro

    ISSN: 1066-6192
    Vydavateľské údaje: IEEE 01.03.2015
    “…Routing is a key parameter in the design of the interconnection network of large parallel computers…”
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    A Cluster-Based Approach to Consensus Based Distributed Task Allocation Autor Smith, Darren, Wetherall, Jodie, Woodhead, Stephen, Adekunle, Andrew

    ISSN: 1066-6192
    Vydavateľské údaje: IEEE 01.02.2014
    “…This paper presents a novel extension to the Consensus-Based Bundle Algorithm (CBBA), which we have named Cluster-Formed Consensus-Based Bundle Algorithm…”
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    Dimension Reduction Methods for Collaborative Mobile Gossip Learning Autor Berta, Arpad, Hegedus, Istvan, Jelasity, Mark

    ISSN: 2377-5750
    Vydavateľské údaje: IEEE 01.02.2016
    “…Decentralized learning algorithms are very sensitive to the size of the raw data records due to the resulting large communication cost…”
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