Abstract
The recent trend of Processing-in-Memory (PIM) promises to tackle the memory and energy wall problems lurking in the data movement around the memory hierarchy, like in data analysis applications. In this paper, we present our vision on how database systems can embrace PIM in query processing. We share with the community an empirical analysis of the pros/cons of PIM in three main query operators to discuss our vision. We also present promising results of our ongoing work to build a PIM-aware query scheduler that improved query execution in almost 3\(\times \) and reduced energy consumption in at least 25%. We complete our discussion with challenges and opportunities to foster research impulses in the co-design of Database-PIM.
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This work was partially supported by the Serrapilheira Institute (grant number Serra-1709-16621).
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Kepe, T.R., Almeida, E.C., Alves, M.A.Z., Meira, J.A. (2019). Database Processing-in-Memory: A Vision. In: Hartmann, S., Küng, J., Chakravarthy, S., Anderst-Kotsis, G., Tjoa, A., Khalil, I. (eds) Database and Expert Systems Applications. DEXA 2019. Lecture Notes in Computer Science(), vol 11706. Springer, Cham. https://doi.org/10.1007/978-3-030-27615-7_32
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