A performance predictor for implementation selection of parallelized static and temporal graph algorithms-Reference-Cited by-同舟云学术

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A performance predictor for implementation selection of parallelized static and temporal graph algorithms

Published:2021-04-26 Issue:2 Volume:34 Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency and Computation

Author:

Rehman Akif¹^ORCID,Ahmad Masab¹,Khan Omer¹

Affiliation:

1. Electrical and Computer Engineering University of Connecticut Storrs Connecticut USA

Funder

National Science Foundation

U.S. Naval Research Laboratory

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.6267

Reference36 articles.

1. Autonomous cars: The tension between occupant experience and intersection capacity

2. KwakH LeeC ParkH MoonS. What is Twitter a social network or a news media? Paper presented at: Proceedings of the 19th International Conference on World Wide Web WWW '10;2010:591‐600; ACM New York NY.

3. End to end learning for self‐driving cars;Bojarski M;CoRR,2016

4. DengD ShahabiC DemiryurekU ZhuL YuR LiuY. Latent space model for road networks to predict time‐varying traffic. Paper presented at: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining;2016:1525‐1534; ACM New York NY.

5. SantoroN QuattrociocchiW FlocchiniP CasteigtsA AmblardF. Time‐varying graphs and social network analysis: temporal indicators and metrics;2011. arXiv preprint arXiv:1102.0629.

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