Parallel Computing

Systems & Applications

Parallel Computing - ISSN 0167-8191
Source Normalized Impact per Paper (SNIP): 1.693 Source Normalized Impact per Paper (SNIP):
SNIP measures contextual citation impact by weighting citations based on the total number of citations in a subject field.
SCImago Journal Rank (SJR): 0.726 SCImago Journal Rank (SJR):
SJR is a prestige metric based on the idea that not all citations are the same. SJR uses a similar algorithm as the Google page rank; it provides a quantitative and a qualitative measure of the journal’s impact.
Impact Factor: 1 (2015) Impact Factor:
The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years.
© Thomson Reuters Journal Citation Reports 2015
5 Year Impact Factor: 1.663 (2015) Five-Year Impact Factor:
To calculate the five year Impact Factor, citations are counted in 2014 to the previous five years and divided by the source items published in the previous five years.
© Journal Citation Reports 2015, Published by Thomson Reuters
Volumes: Volumes 61-70
Issues: 10 issues
ISSN: 01678191

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Description

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 that use multiple nodes and/or multiple accelerators (e.g., GPUs).

Parallel Computing features original research work, tutorial 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. Contributions can cover these technical areas:

  • 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
  • Application 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 including new algorithms or algorithm analysis with demonstrated relevance to real applications using existing or next generation parallel computer architectures.
  • Parallel I/O systems both hardware and software
  • Networking technology for support of high-speed computing demonstrating the impact of high-speed computation on parallel applications

Please note, we generally do not publish papers about single GPU or single node (typically one address space) systems.

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