A Highly Parallel Fine-Grained Sort-Merge Join on Near Memory Computing

Po Yen Lin, Yen Shi Kuo, Bo Cheng Lai

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In-time processing of database system is imperative to reveal the hidden information. JOIN operation is critical in data analysis, as it occupies almost half of the average execution time in the standard TPC-H benchmark for database processing. In modern databases, transferring data between computing engines and system memory has become one of the main performance challenges. Previous works of Near Memory Computing (NMC) alleviated the costly data transfer, however, the designs still pose inefficiency in terms of processing flow and data management. In this paper, we propose FG-SMJ: a highly parallel fine-grained sort-merge join on near memory computing. The novel data layout allows us to access data from memory chips with fine-grained chip-level parallelism and exploit memory bandwidth. Compared with previous NMC designs, the proposed FG-SMJ attains 3.08x speedup.

Original languageEnglish
Title of host publicationIEEE International Symposium on Circuits and Systems, ISCAS 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2566-2570
Number of pages5
ISBN (Electronic)9781665484855
DOIs
StatePublished - 2022
Event2022 IEEE International Symposium on Circuits and Systems, ISCAS 2022 - Austin, United States
Duration: 27 May 20221 Jun 2022

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
Volume2022-May
ISSN (Print)0271-4310

Conference

Conference2022 IEEE International Symposium on Circuits and Systems, ISCAS 2022
Country/TerritoryUnited States
CityAustin
Period27/05/221/06/22

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