@inproceedings{BernhardtKochPetrov2023,
  author    = {Bernhardt, Arthur and Koch, Andreas and Petrov, Ilia},
  title     = {pimDB: From main-memory DBMS to processing-in-memory DBMS-engines on intelligent memories},
  booktitle = {DaMoN '23: Proceedings of the 19th International Workshop on Data Management on New Hardware, 18-23 June 2023, Seattle},
  doi       = {10.1145/3592980.3595312},
  institution = {Informatik},
  pages     = {44 -- 52},
  year      = {2023},
  abstract  = {The performance and scalability of modern data-intensive systems are limited by massive data movement of growing datasets across the whole memory hierarchy to the CPUs. Such traditional processor-centric DBMS architectures are bandwidth- and latency-bound. Processing-in-Memory (PIM) designs seek to overcome these limitations by integrating memory and processing functionality on the same chip. PIM targets near- or in-memory data processing, leveraging the greater in-situ parallelism and bandwidth. In this paper, we introduce pimDB and provide an initial comparison of processor-centric and PIM-DBMS approaches under different aspects, such as scalability and parallelism, cache-awareness, or PIM-specific compute/bandwidth tradeoffs. The evaluation is performed end-to-end on a real PIM hardware system from UPMEM.},
  language  = {en}
}