@inproceedings{4cadc2bb50b447a89c95bf5c4d7abb01,
title = "A Portable and Heterogeneous LU Factorization on IRIS",
abstract = "Here, the IRIS programming model is evaluated as a method to improve performance portability for heterogeneous systems that use LU matrix factorization. LU (lower-upper) factorization is considered one of the most important numerical linear algebra operations used in multiple high-performance computing and scientific applications. IRIS enables the separation of the algorithm{\textquoteright}s definition from the tuning by using tasks + dependencies. This considerably reduces the effort required to achieve performance portability on heterogeneous systems. One IRIS code can use different settings depending on the underlying hardware features. Different configurations are evaluated on two different heterogeneous systems to achieve important speedups for the reference code with minimal changes to the source code.",
keywords = "CPU, GPU, Heterogeneity, IRIS, LU factorization, Performance portability, Tasking",
author = "Pedro Valero-Lara and Jungwon Kim and Vetter, {Jeffrey S.}",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 28th International European Conference on Parallel and Distributed Computing , Euro-Par 2022 ; Conference date: 22-08-2022 Through 26-08-2022",
year = "2023",
doi = "10.1007/978-3-031-31209-0_2",
language = "English",
isbn = "9783031312083",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "17--31",
editor = "Jeremy Singer and Yehia Elkhatib and {Blanco Heras}, Dora and Patrick Diehl and Nick Brown and Aleksandar Ilic",
booktitle = "Euro-Par 2022",
}