@inproceedings{6b31b4b71c114ee7ae57a0e7a789ceb4,
title = "Systematic reduction of data movement in algebraic multigrid solvers",
abstract = "Algebraic Multigrid (AMG) solvers find wide use in scientific simulation codes. Their ideal computational complexity makes them especially attractive for solving large problems on parallel machines. However, they also involve a substantial amount of data movement, posing challenges to performance and scalability. In this paper, we present an algorithm that provides a systematic means of reducing data movement in AMG. The algorithm operates by gathering and redistributing the problem data to reduce the need to move it on the communication-intensive coarse grid portion of AMG. The data is gathered in a way that ensures data locality by keeping data movement confined to specific regions of the machine. Any decision to gather data is made systematically through the means of a performance model. This approach results in substantial speedups on a multicore cluster when using AMG to solve a variety of test problems.",
author = "Hormozd Gahvari and William Gropp and Jordan, {Kirk E.} and Martin Schulz and Yang, {Ulrike Meier}",
year = "2013",
doi = "10.1109/IPDPSW.2013.164",
language = "English (US)",
isbn = "9780769549798",
series = "Proceedings - IEEE 27th International Parallel and Distributed Processing Symposium Workshops and PhD Forum, IPDPSW 2013",
publisher = "IEEE Computer Society",
pages = "1675--1682",
booktitle = "Proceedings - IEEE 27th International Parallel and Distributed Processing Symposium Workshops and PhD Forum, IPDPSW 2013",
note = "2013 IEEE 37th Annual Computer Software and Applications Conference, COMPSAC 2013 ; Conference date: 22-07-2013 Through 26-07-2013",
}