A novel multi-level integrated roofline model approach for performance characterization
: Tuomas Koskela, Zakhar Matveev, Charlene Yang, Adetokunbo Adedoyin, Roman Belenov, Philippe Thierry, Zhengji Zhao, Rahulkumar Gayatri, Hongzhang Shan, Leonid Oliker, Jack Deslippe, Ron Green, Samuel Williams
: Rio Yokota, Michèle Weiland, David Keyes, Carsten Trinitis
: International Conference on High Performance Computing
Publisher: Springer Verlag
: 2018
: Lecture Notes in Computer Science
: High Performance Computing
: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
: Lecture Notes in Computer Science
: 10876
: 226
: 245
: 20
: 978-3-319-92039-9
: 978-3-319-92040-5
: 0302-9743
DOI: https://doi.org/10.1007/978-3-319-92040-5_12
: https://research.utu.fi/converis/portal/detail/Publication/32081756
With energy-efficient architectures, including accelerators and many-core processors, gaining traction, application developers face the challenge of optimizing their applications for multiple hardware features including many-core parallelism, wide processing vector-units and on-chip high-bandwidth memory. In this paper, we discuss the development and utilization of a new application performance tool based on an extension of the classical roofline-model for simultaneously profiling multiple levels in the cache-memory hierarchy. This tool presents a powerful visual aid for the developer and can be used to frame the many-dimensional optimization problem in a tractable way. We show case studies of real scientific applications that have gained insights from the Integrated Roofline Model.
