JOURNAL OF SUPERCOMPUTING - Journal - Bridge of Knowledge

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JOURNAL OF SUPERCOMPUTING

ISSN:

0920-8542

eISSN:

1573-0484

Disciplines
(Field of Science):

  • Ethnology and cultural anthropology (Humanities)
  • Automation, electronics, electrical engineering and space technologies (Engineering and Technology)
  • Information and communication technology (Engineering and Technology)
  • Biomedical engineering (Engineering and Technology)
  • Heritage protection and conservation of monuments (Engineering and Technology)
  • Management and quality studies (Social studies)
  • Computer and information sciences (Natural sciences)

Ministry points: Help

Ministry points - current year
Year Points List
Year 2024 70 Ministry scored journals list 2024
Ministry points - previous years
Year Points List
2024 70 Ministry scored journals list 2024
2023 70 Ministry Scored Journals List
2022 70 Ministry Scored Journals List 2019-2022
2021 70 Ministry Scored Journals List 2019-2022
2020 70 Ministry Scored Journals List 2019-2022
2019 70 Ministry Scored Journals List 2019-2022
2018 20 A
2017 20 A
2016 20 A
2015 20 A
2014 20 A
2013 20 A
2012 15 A
2011 15 A
2010 20 A

Model:

Hybrid

Points CiteScore:

Points CiteScore - current year
Year Points
Year 2022 5.4
Points CiteScore - previous years
Year Points
2022 5.4
2021 4.8
2020 4.6
2019 3.9
2018 3.2
2017 3.3
2016 3.4
2015 2.8
2014 2
2013 1.8
2012 1.5
2011 1.5

Impact Factor:

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total: 7

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Catalog Journals

Year 2021
Year 2019
Year 2018
  • Improving all-reduce collective operations for imbalanced process arrival patterns
    Publication

    Two new algorithms for the all-reduce operation optimized for imbalanced process arrival patterns (PAPs) are presented: (1) sorted linear tree, (2) pre-reduced ring as well as a new way of online PAP detection, including process arrival time estimations, and their distribution between cooperating processes was introduced. The idea, pseudo-code, implementation details, benchmark for performance evaluation and a real case example...

    Full text available to download

  • Parallelization of large vector similarity computations in a hybrid CPU+GPU environment
    Publication

    The paper presents design, implementation and tuning of a hybrid parallel OpenMP+CUDA code for computation of similarity between pairs of a large number of multidimensional vectors. The problem has a wide range of applications, and consequently its optimization is of high importance, especially on currently widespread hybrid CPU+GPU systems targeted in the paper. The following are presented and tested for computation of all vector...

    Full text available to download

Year 2017
Year 2013
Year 2010

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