@inproceedings{223d54f04d3c4f7aa5ee3695c997aeb2,
title = "Enabling Relational Database Analytical Processing in Bulk-Bitwise Processing-In-Memory",
abstract = "Bulk-bitwise processing-in-memory (PIM), an emerging computational paradigm utilizing memory arrays as computational units, has been shown to benefit database applications. This paper demonstrates how GROUP-BY and JOIN, database operations not supported by previous works, can be performed efficiently in bulk-bitwise PIM for relational database analytical processing. We extend the gem5 simulator and evaluated our hardware modifications on the Star Schema Benchmark. We show that compared to previous works, our modifications improve (on average) execution time by 1.83×, energy by 4.31×, and the system's lifetime by 3.21×. We also achieved a speedup of 4.65× over MonetDB, a modern state-of-the-art in-memory database.",
keywords = "Database, Memristors, OLAP, Processing-in-memory",
author = "Ben Perach and Ronny Ronen and Shahar Kvatinsky",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 36th IEEE International System-on-Chip Conference, SOCC 2023 ; Conference date: 05-09-2023 Through 08-09-2023",
year = "2023",
doi = "10.1109/SOCC58585.2023.10256706",
language = "الإنجليزيّة",
series = "International System on Chip Conference",
editor = "Jurgen Becker and Andrew Marshall and Tanja Harbaum and Amlan Ganguly and Fahad Siddiqui and Kieran McLaughlin",
booktitle = "Proceedings - 2023 IEEE 36th International System-on-Chip Conference, SOCC 2023",
}