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Journal of Flow Visualization and Image Processing
Главный редактор: Krishnamurthy Muralidhar (open in a new tab)

Выходит 4 номеров в год

ISSN Печать: 1065-3090

ISSN Онлайн: 1940-4336

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. 2017 Journal Citation Reports (Clarivate Analytics, 2018) IF: 0.6 The Immediacy Index is the average number of times an article is cited in the year it is published. The journal Immediacy Index indicates how quickly articles in a journal are cited. Immediacy Index: 0.6 The Eigenfactor score, developed by Jevin West and Carl Bergstrom at the University of Washington, is a rating of the total importance of a scientific journal. Journals are rated according to the number of incoming citations, with citations from highly ranked journals weighted to make a larger contribution to the eigenfactor than those from poorly ranked journals. Eigenfactor: 0.00013 The Journal Citation Indicator (JCI) is a single measurement of the field-normalized citation impact of journals in the Web of Science Core Collection across disciplines. The key words here are that the metric is normalized and cross-disciplinary. JCI: 0.14 SJR: 0.201 SNIP: 0.313 CiteScore™:: 1.2 H-Index: 13

Indexed in

VISUALIZATION OF PARALLEL AND DISTRIBUTED PROGRAMS

Том 21, Выпуск 1-4, 2014, pp. 1-11
DOI: 10.1615/JFlowVisImageProc.v21.i1-4.20
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Краткое описание

The article is aimed at researching problems of scientific data visualization system optimization in order to formulate an approach to their effective solution concerning the application on high-performance multiprocessor computers. A single-processor version of a ScientificVR® (SVR) visualization package with a set of different types of visualization, which can be well used for processing data obtained through simulation using distributed computer systems, is presented. An approach to the SVR scientific data visualization system optimization to provide the ability to be applicable on multiprocessor computers with the most efficient and flexible performance is proposed.

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