Analyzing the I/O Performance of Post-Hoc Visualization of Huge Simulation Datasets on the K Computer - C. Inacio, Eduardo; Nonaka, Jorji; Ono, Kenji; A. R. Dantas, Mario (Anais do Simpósio em Sistemas Computacionais de Alto Desempenho (SSCAD), 2017)
As computational science simulations produce ever increasing volumes of data, executing part or even the entire visualization pipeline in the supercomputer side becomes more a requirement than an option. Given the uniqueness of the high performance K computer architecture, the HIVE visualization framework was developed, focusing on meeting visualization and data analysis demands of scientists and engineers. In this paper, we present an analysis on the input/output (I/O) performance of post-hoc visualization. The contribution of this research work is characterized by an analysis of a set of empirical study cases considering huge simulation datasets using HIVE on the K computer. Results from the experimental effort, using a dataset produced by a real-world global climate simulation, provide a differentiated knowledge on the impact of dataset partitioning parameters in the I/O performance of large-scale visualization systems, and highlight challenges and opportunities for performance optimizations.