Fast-Tracking Scalability Analysis: The PaScal Paramount Approach - Maia, Reilta Christine Dantas; Xavier-de-Souza, Samuel (Anais do Simpósio em Sistemas Computacionais de Alto Desempenho (SSCAD); 2025: Anais do XXVI Simpósio em Sistemas Computacionais de Alto DesempenhoDO - 10.5753/sscad.2025.16734, 2025)
Scalability analysis of High-Performance Computing applications is essential, but its process is time-consuming and costly. This work introduces PaScal Paramount, a new feature of the PaScal Analyzer tool that accelerates this analysis by estimating the total performance from the execution of a small fraction of the parallel code. Experiments demonstrated that the approach reduces analysis time by up to 89% while maintaining low estimation error and generating performance patterns faithful to the full execution. The feature offers an adjustable trade-off between speed and accuracy, proving to be an effective solution for gaining rapid insights into the behavior of applications, thereby guiding their optimization process.