Parallel Computing

  in Journal   Posted on September 23, 2020

Journal Ranking & Metrics

G2R Score : 2.64
G2R H-Index : 8
JCR Impact Factor : 1.119
Scopus Citescore : 2.9
SCIMAGO H-index : 63
Guide2Research Overall Ranking : 400

Journal Information

ISSN : 0167-8191
Publisher :
Periodicity : Monthly
Editors-in-Chief : U.V. Catalyurek
Journal & Submission Website :

Top Scientists who published in this Journal

Number of top scientists* : 19
Documents published by top scientists* : 30
* Based on data published during the last three years.

Aims & Scope of the Journal

Parallel Computing is an international journal presenting the practical use of parallel computer systems, including high performance architecture, system software, programming systems and tools, and applications. Within this context the journal covers all aspects of high-end parallel computing from single homogeneous or heterogenous computing nodes to large-scale multi-node systems. Parallel Computing features original research work and review articles as well as novel or illustrative accounts of application experience with (and techniques for) the use of parallel computers. We also welcome studies reproducing prior publications that either confirm or disprove prior published results. Particular technical areas of interest include, but are not limited to: System software for parallel computer systems including programming languages (new languages as well as compilation techniques), operating systems (including middleware), and resource management (scheduling and load-balancing). Enabling software including debuggers, performance tools, and system and numeric libraries. General hardware (architecture) concepts, new technologies enabling the realization of such new concepts, and details of commercially available systems Software engineering and productivity as it relates to parallel computing Applications (including scientific computing, deep learning, machine learning) or tool case studies demonstrating novel ways to achieve parallelism Performance measurement results on state-of-the-art systems Approaches to effectively utilize large-scale parallel computing…

Special Issues on this journal