Open AccessAtTune: A Heuristic based Framework for Parallel Applications Autotuning
Author(s) -
Hiago Mayk G. de A. Rocha,
Janaína Schwarzrock,
Monica Pereira,
Lucas Mello Schnorr,
Philippe O. A. Navaux,
Arthur F. Lorenzon,
Antonio Carlos Schneider Beck Filho
Publication year - 2020
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5753/sbesc_estendido.2020.13105
Subject(s) - computer science , scalability , synchronization (alternating current) , distributed computing , efficient energy use , heuristic , multi core processor , parallel computing , embedded system , operating system , computer network , channel (broadcasting) , artificial intelligence , electrical engineering , engineering
Several aspects limit the scalability of parallel applications, e.g., off-chip bus saturation and data synchronization. Moreover, the high cost of cooling HPC systems, which can outweigh the cost of developing the system itself, has pushed the parallel application’s execution to another level of requirements, in terms of performance and energy. In this work, we propose AtTune: a heuristic-based framework for tuning the number of processes/threads and CPU frequency to optimize the parallel applications’ execution. AtTune is transparent for the user, independent of the input size, and it optimizes for different parallel programming models. We evaluated our proposed solution considering five well-known kernels implemented in MPI and OpenMP. Experimental results on two real multi-core systems showed that AtTune improves up to 36%, 11%, and 32% the energy efficiency, performance, and Energy-Delay Product, respectively.