Application optimization with Cache-aware Roofline Model and Intel oneAPI tools
HANDS ON SESSION
Application optimization with Cache-aware Roofline Model and Intel oneAPI tools
In this tutorial, we will introduce the Cache-aware Roofline Model (CARM) and expose its principles when modelling the performance of Intel CPU and GPU devices. We will also showcase how CARM implementation in Intel® Advisor can be used to drive the application optimization. For this purpose, we will rely on epistasis detection as a case-study, which is an important application in bioinformatics. For lntel GPUs, we will show how CARM can be used to detect execution bottlenecks and provide useful hints on which type of optimizations to apply to fully exploit device capabilities. The guidelines provided by CARM were fundamental to achieve the speedups of more than 20x when compared to the baseline code.
Speaker(s)
Aleksandar Ilic
Aleksandar Ilic is an Assistant Professor at the Instituto Superior Técnico (IST), Universidade de Lisboa, and a Senior Researcher of the INESC-ID, Portugal. He contributed to more than 50 scientific publications. His research interests include high-performance and energy-efficient computing and modeling of heterogeneous systems.
Diogo Marques
Diogo Marques is a member of the HPCAS group at Instituto de Engenharia de Sistemas e Computadores R&D (INESC-ID). His research interests include the modeling of multi-core and heterogeneous systems. His work contributed to improve the accuracy of Cache-aware Roofline Model, by proposing the memory metrics and scaled roofs presented in Intel Advisor.
Rafael Campos
Rafael Campos is a young researcher at Instituto de Engenharia de Sistemas e Computadores R&D (INESC-ID), as part of the HPCAS group. His main interests are performance modeling of heterogeneous systems, with focus on performance optimization of bioinformatics applications and roofline modeling of high-performance heterogeneous CPU/GPU systems.
