Suchergebnisse - Algorithm Parallelization. Keywords CUDA

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  1. 1

    A Parallelization of Non-Serial Polyadic Dynamic Programming on GPU von Diwan, Tausif, Tembhurne, Jitendra

    ISSN: 1330-1136, 1846-3908
    Veröffentlicht: Sveuciliste U Zagrebu 01.06.2019
    Veröffentlicht in Journal of computing and information technology (01.06.2019)
    “… Parallelization of Non-Serial Polyadic Dynamic Programming (NPDP) on high-throughput manycore architectures, such as NVIDIA GPUs, suffers from load imbalance, i.e …”
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    Journal Article Paper
  2. 2

    Parallelization of heterogeneous reactor calculations on a graphics processing unit von Malofeev, V. M., Pal’shin, V. A.

    ISSN: 1063-7788, 1562-692X
    Veröffentlicht: Moscow Pleiades Publishing 01.12.2016
    Veröffentlicht in Physics of atomic nuclei (01.12.2016)
    “… Parallelization is applied to the neutron calculations performed by the heterogeneous method on a graphics processing unit …”
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    Journal Article
  3. 3

    Parallel alpha-beta algorithm on the GPU von Strnad, D., Guid, N.

    ISBN: 1612848974, 9781612848976
    ISSN: 1330-1012, 1330-1136, 1846-3908
    Veröffentlicht: IEEE 01.12.2011
    “… In the paper we present the parallel implementation of the alpha-beta algorithm running on the graphics processing unit (GPU …”
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    Tagungsbericht Journal Article Paper
  4. 4

    rapidGSEA: Speeding up gene set enrichment analysis on multi-core CPUs and CUDA-enabled GPUs von Hundt, Christian, Hildebrandt, Andreas, Schmidt, Bertil

    ISSN: 1471-2105, 1471-2105
    Veröffentlicht: London BioMed Central 23.09.2016
    Veröffentlicht in BMC bioinformatics (23.09.2016)
    “… Background Gene Set Enrichment Analysis (GSEA) is a popular method to reveal significant dependencies between predefined sets of gene symbols and observed …”
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    Journal Article
  5. 5

    GPU based numerical simulation of core shooting process von Zhang, Yi-zhong, Lu, Gao-chun, Ni, Chang-jiang, Jing, Tao, Yang, Lin-long, Wu, Qin-fang

    ISSN: 1672-6421, 2365-9459, 1672-6421
    Veröffentlicht: Singapore Springer Singapore 01.09.2017
    Veröffentlicht in China foundry (01.09.2017)
    “… The parallel algorithm based on the Compute Unified Device Architecture(CUDA) platform can significantly decrease computing time by multi …”
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    Journal Article
  6. 6

    Optimizing the Bellman-Ford Algorithm Using GPU Parallelization von Cholla, Dr. Raman

    ISSN: 2582-3930, 2582-3930
    Veröffentlicht: 12.05.2025
    “… ABSTRACT The Bellman-Ford algorithm's temporal complexity of O(VE) renders it ineffective for big and dense networks, which is a serious computational disadvantage …”
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    Journal Article
  7. 7

    Removing duplicate reads using graphics processing units von Manconi, Andrea, Moscatelli, Marco, Armano, Giuliano, Gnocchi, Matteo, Orro, Alessandro, Milanesi, Luciano

    ISSN: 1471-2105, 1471-2105
    Veröffentlicht: London BioMed Central 08.11.2016
    Veröffentlicht in BMC bioinformatics (08.11.2016)
    “… Background During library construction polymerase chain reaction is used to enrich the DNA before sequencing. Typically, this process generates duplicate read …”
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    Journal Article
  8. 8

    HECTOR: a parallel multistage homopolymer spectrum based error corrector for 454 sequencing data von Wirawan, Adrianto, Harris, Robert S, Liu, Yongchao, Schmidt, Bertil, Schröder, Jan

    ISSN: 1471-2105, 1471-2105
    Veröffentlicht: London BioMed Central 06.05.2014
    Veröffentlicht in BMC bioinformatics (06.05.2014)
    “… In this algorithm, for the first time we have investigated a novel homopolymer spectrum based approach to handle homopolymer insertions or deletions, which are the dominant sequencing errors in 454 pyrosequencing reads …”
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    Journal Article
  9. 9

    CUDASW++ 3.0: accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions von Liu, Yongchao, Wirawan, Adrianto, Schmidt, Bertil

    ISSN: 1471-2105, 1471-2105
    Veröffentlicht: London BioMed Central 04.04.2013
    Veröffentlicht in BMC bioinformatics (04.04.2013)
    “… For the GPU computation, we have investigated for the first time a GPU SIMD parallelization, which employs CUDA PTX SIMD video instructions to gain more data parallelism beyond the SIMT execution model …”
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    Journal Article