In the landscape of exascale computing collaborative research campaigns are conducted as co-design activities of loosely coordinated experiments. But the higher level context and the knowledge of individual experimental activity is lost over time. We undertook a knowledge capture and representation aid called Campaign Knowledge Network(CKN), a co-design design and analysis tool. We demonstrate that CKN can satisfy the Hoarde abstraction and can distill campaign context from runtime information thereby creating a knowledge resource upon which analysis tools can run to provide more efficient experimentation
@article{arxiv.2112.03435,
title = {Campaign Knowledge Network: Building Knowledge for Campaign Efficiency},
author = {Sachith Withana and Kshitij Mehta and Matthew Wolf and Beth Plale},
journal= {arXiv preprint arXiv:2112.03435},
year = {2021}
}