Ana Luisa Veroneze Solórzano
Lucas Leandro Nesi
ABSTRACT
Parallel programs regularly face performance issues due to inefficient load distribution. Before redistributing load to avoid idle processes, it is essential to identify and measure the imbalance. In this paper, we present our approach to investigate load imbalance by using performance visualization and five imbalance metrics. We analyzed Ondes3D, an earthquake simulator with time-spatial imbalance, used to predict and better understand the impact of disasters. With the Ondes3D computational signature, we obtained further information on load distribution during the application’s iterations to understand how the metrics measures evolve throughout execution. Our approach can be useful to other imbalanced applications, identifying when the load is unevenly processed and how severe is the imbalance during each timestep. As future work, we plan to compare our chosen metrics with others that may present different results.
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- Using Visualization of Performance Data to Investigate Load Imbalance of a Geophysics Parallel Application
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