TY  - CPAPER
U1  - Konferenzveröffentlichung
A1  - Bernhardt, Arthur
A1  - Koch, Andreas
A1  - Petrov, Ilia
T1  - pimDB: From main-memory DBMS to processing-in-memory DBMS-engines on intelligent memories
T2  - DaMoN '23: Proceedings of the 19th International Workshop on Data Management on New Hardware, 18-23 June 2023, Seattle
N2  - 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.
Y1  - 2023
U6  - https://doi.org/10.1145/3592980.3595312
DO  - https://doi.org/10.1145/3592980.3595312
SP  - 44
EP  - 52
S1  - 9
PB  - Association for Computing Machinery
CY  - New York
ER  -