Hanjun Kim  

Associate Professor
School of Electrical and Electronic Engineering, Yonsei University

Ph.D. 2013, Department of Computer Science, Princeton University

Office: Engineering Hall #3-C415
Phone: +82-2-2123-2770
Email: first_name at yonsei.ac.kr
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Refereed International Conference Publications

Design and Analysis of a Processing-in-DIMM Join Algorithm: A Case Study with UPMEM DIMMs [abstract] (ACM)
Chaemin Lim, Suhyun Lee, Jinwoo Choi, Jounghoo Lee, Seongyeon Park, Hanjun Kim, Jinho Lee, and Youngsok Kim
2023 ACM SIGMOD International Conference on Management of Data (SIGMOD), June 2023.

Modern dual in-line memory modules (DIMMs) support processing-in-memory (PIM) by implementing in-DIMM processors (IDPs) located near memory banks. PIM can greatly accelerate in-memory join, whose performance is frequently bounded by main-memory accesses, by offloading the operations of join from host central processing units (CPUs) to the IDPs. As real PIM hardware has not been available until very recently, the prior PIM-assisted join algorithms have relied on PIM hardware simulators which assume fast shared memory between the IDPs and fast inter-IDP communication; however, on commodity PIM-enabled DIMMs, the IDPs do not share memory and demand the CPUs to mediate inter-IDP communication. Such discrepancies in the architectural characteristics make the prior studies incompatible with the DIMMs. Thus, to exploit the high potential of PIM on commodity PIM-enabled DIMMs, we need a new join algorithm designed and optimized for the DIMMs and their architectural characteristics. In this paper, we design and analyze Processing-In-DIMM Join (PID-Join), a fast in-memory join algorithm which exploits UPMEM DIMMs, currently the only publicly-available PIM-enabled DIMMs. The DIMMs impose several key challenges on efficient acceleration of join including the shared-nothing nature and limited compute capabilities of the IDPs, the lack of hardware support for fast inter-IDP communication, and the slow IDP-wise data transfers between the IDPs and the main memory. PID-Join overcomes the challenges by prototyping and evaluating hash, sort-merge, and nested-loop algorithms optimized for the IDPs, enabling fast inter-IDP communication using host CPU cache streaming and vector instructions, and facilitating fast rank-wise data transfers between the IDPs and the main memory. Our evaluation using a real system equipped with eight UPMEM DIMMs and 1,024 IDPs shows that PID-Join greatly improves the performance of in-memory join over various CPU-based in-memory join algorithms.