Boost Epistasis Detection with Cache-Aware Roofline Model
Speaker: Aleksandar Ilic, Instituto Superior Técnico (IST), Universidade de Lisboa & INESC-ID
In the first part of this talk, we introduce the Cache-aware Roofline Model (CARM) and expose its basic principles when modeling the performance upper-bounds of a processor. We also discuss our recent research contributions in extending the model insightfulness with application-driven CARM, as well as applying the CARM principles to model power consumption and energy efficiency upper-bounds.
In the second part of this talk, we rely on CARM implementation in Intel® Advisor to showcase its ability to drive the optimization of epistasis detection, an important application in bioinformatics. For both Intel® CPU and GPU devices, we demonstrate 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 on six-core Intel® CPUs and Gen 9.5 GPUs.
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Supercomputing 2020 (SC20) Recorded Sessions on oneAPI
- C++ for Heterogeneous Programming: oneAPI
- Performance Tuning with the Roofline Model on GPUs and CPUs
- Panel: The oneAPI Software Abstraction for Heterogeneous Computing