| Outline of Final Research Achievements |
The problem of this project arose from the experience in another large-scale data stream analysis project. That is, the behavior of analysis programs can vary significantly depending on the characteristics of the input data. Such tendencies can also be observed in other applications. In particular, in sparse matrix computations, it is quite common to switch the preconditioners based on the characteristics of the input matrix. Therefore, the collaboration with experts in sparse matrix computations is expected to be a great way to attack the project target. In the COVID-19 pandemic, the collaboration became difficult. Therefore, we explored various applications beyond data stream analysis, and attempted to model the target based on their characteristic differences. However, we were unable to obtain a clear model by the end of this project.
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