World's Best Scientists 2026 revealed!
Parallel Computing
H-index 12

Parallel Computing

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Computer Science 519 46 43 11

Additional Metrics

Number of Best Scientists*: 70
Documents by Best Scientists*: 59
Top 100 Ranked Scientists*: 3
SCIMAGO H-index: 72
SCIMAGO SJR: 0.541
Impact Factor: 2.1

Overview

Top Research Topics at Parallel Computing?

The journal focuses on Vector processor and Computer hardware.

  • Vector processor (100.00%)
  • Computer hardware (100.00%)

Papers citation over time

Insufficient data to conduct the analysis

The top authors publishing in Parallel Computing (based on the number of publications) are:

  • Corana A (1 papers) published 1 paper at the last edition,
  • Rolando C (1 papers) published 1 paper at the last edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Only papers with recognized affiliations are considered

Insufficient data to conduct the analysis

Publication chance based on affiliation

Insufficient data to conduct the analysis

Returning Authors Index

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The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

  • Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
  • Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
  • Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
  • Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
  • Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Future Trends in Parallel Computing

With the advancement in technology, Parallel computing continues to evolve to meet the emerging needs of various fields. To understand the future of Parallel Computing, one can study the emerging trends and anticipated breakthroughs in this domain. With the blending of AI and Machine Learning algorithms with Parallel computing, there is a projection of a more efficient and effective processing capability. Moreover, the use of advanced hardware accelerators such as GPUs for parallel processing significantly increases computational power and speed. Cloud-based parallel computing is also another emerging trend. By leveraging cloud resources and infrastructure, small organizations and individuals can access parallel computing resources without the need for significant investments into the complex hardware setups that parallel computing often requires. To delve into these potentials and explore different learning paths to keep up with these trends, you may consider enrolling in one of the best teaching credential programs in Hawaii. These programs not only offer comprehensive insights into the field of parallel computing but also provide you an opportunity to understand the upcoming trends and how to stay abreast in this rapidly evolving technological landscape.

Top Publications

  • Porting WarpX to GPU-accelerated platforms

    Andrew Myers;Ann S. Almgren;L. D. Amorim;John B. Bell

    (2021)
    43 Citations
  • OpenMP application experiences: Porting to accelerated nodes

    Seonmyeong Bak;Colleen Bertoni;Swen Boehm;Reuben Budiardja

    (2022)
    29 Citations
  • GPU algorithms for Efficient Exascale Discretizations

    Ahmad Abdelfattah;Valeria Barra;Natalie Beams;Ryan Bleile

    (2021)
    22 Citations
  • Porting hypre to heterogeneous computer architectures: Strategies and experiences

    Robert D. Falgout;Ruipeng Li;Björn Sjögreen;Lu Wang

    (2021)
    19 Citations
  • Multiscale modeling and cinematic visualization of photosynthetic energy conversion processes from electronic to cell scales.

    Melih Sener;Stuart A Levy;John E. Stone;Andrew J Christensen

    (2021)
    14 Citations
  • A case study on parallel HDF5 dataset concatenation for high energy physics data analysis

    (2021)
    13 Citations
  • Routing brain traffic through the von Neumann bottleneck: Efficient cache usage in spiking neural network simulation code on general purpose computers

    (2021)
    13 Citations
  • HBPFP-DC: A parallel frequent itemset mining using Spark

    Yaling Xun;Jifu Zhang;Haifeng Yang;Xiao Qin

    (2021)
    12 Citations
  • A novel method of grouping target paths for parallel programs

    (2020)
    12 Citations
  • Dynamic power management for value-oriented schedulers in power-constrained HPC system

    Nirmal Kumbhare;Ali Akoglu;Aniruddha Marathe;Salim Hariri

    (2020)
    12 Citations

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Best Scientists Contributing to This Journal

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