Patterns for High Performance Multiscale Computing
- Submitting institution
-
Brunel University London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 061-191357-21096
- Type
- D - Journal article
- DOI
-
10.1016/j.future.2018.08.045
- Title of journal
- Future Generation Computer Systems
- Article number
- -
- First page
- 335
- Volume
- 91
- Issue
- -
- ISSN
- 0167-739X
- Open access status
- Compliant
- Month of publication
- September
- Year of publication
- 2018
- URL
-
https://www.sciencedirect.com/science/article/pii/S0167739X18300669?via%3Dihub
- Supplementary information
-
https://ars.els-cdn.com/content/image/1-s2.0-S0167739X18300669-mmc1.pdf
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
14
- Research group(s)
-
1 - Artificial Intelligence (AI)
- Citation count
- 8
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The paper is published in FGCS that is ranked 8th out of 105 journals in Computer Science, Theory and Methods (JCR 2018). It is considered the main theory paper in the ComPat project (€4M, 671564), and its results directly inform work in the VECMA project (€4M, 800925). Concepts informed the categorisations used in a 2019 review paper on coupling toolkits (https://doi.org/10.1098/rsta.2018.0147).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
