NPC: A <b>N</b>on-Conflicting <b>P</b>rocessing-in-Memory <b>C</b>ontroller in DDR Memory Systems

Processing-in-Memory (PIM) has emerged as a promising solution to address the memory wall problem. Existing memory interfaces must support new PIM commands to utilize PIM, making the definition of PIM commands according to memory modes a major issue in the development of practical PIM products. For performance and OS-transparency, the memory controller is responsible for changing the memory mode, which requires modifying the controller and resolving conflicts with existing functionalities. Additionally, it must operate to minimize mode transition overhead, which can cause significant performance degradation. In this study, we present NPC, a memory controller designed for mode transition PIM that delivers PIM commands via the DDR interface. NPC issues PIM commands while transparently changing the memory mode with a dedicated scheduling policy that reduces the number of mode transitions with aggregative issuing. Moreover, existing functions, such as refresh, are optimized for PIM operation. We implement NPC in hardware and develop a PIM emulation system to validate it on FPGA platforms. Experimental results reveal that NPC is compatible with existing interfaces and functionality, and the proposed scheduling policy improves performance by 2.2<inline-formula><tex-math notation="LaTeX">$\boldsymbol{\times}$</tex-math></inline-formula> with balanced fairness, achieving up to 97% of the ideal performance. These findings have the potential to aid the application of PIM in real systems and contribute to the commercialization of mode transition PIM.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Computers
Published
2024-10-10
DOI
https://doi.org/10.1109/tc.2024.3477981
Citations
2
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.98
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

NPC: A Non-Conflicting Processing-in-Memory Controller in DDR Memory Systems

Woojae Shin, Chunmyung Park, Minseok Seo, Hyun Kim et al.
2 citations
IEEE Transactions on Computers
Parallel Computing and Optimization Techniques
0.98
article

NPC: A Non-Conflicting Processing-in-Memory Controller in DDR Memory Systems

Woojae Shin, Chunmyung Park, Minseok Seo, Hyun Kim, Sanghyun Lee, Seungyong Lee, Hyuk-Jae Lee
article en
2 citations

Abstract

Processing-in-Memory (PIM) has emerged as a promising solution to address the memory wall problem. Existing memory interfaces must support new PIM commands to utilize PIM, making the definition of PIM commands according to memory modes a major issue in the development of practical PIM products. For performance and OS-transparency, the memory controller is responsible for changing the memory mode, which requires modifying the controller and resolving conflicts with existing functionalities. Additionally, it must operate to minimize mode transition overhead, which can cause significant performance degradation. In this study, we present NPC, a memory controller designed for mode transition PIM that delivers PIM commands via the DDR interface. NPC issues PIM commands while transparently changing the memory mode with a dedicated scheduling policy that reduces the number of mode transitions with aggregative issuing. Moreover, existing functions, such as refresh, are optimized for PIM operation. We implement NPC in hardware and develop a PIM emulation system to validate it on FPGA platforms. Experimental results reveal that NPC is compatible with existing interfaces and functionality, and the proposed scheduling policy improves performance by 2.2<inline-formula><tex-math notation="LaTeX">$\boldsymbol{\times}$</tex-math></inline-formula> with balanced fairness, achieving up to 97% of the ideal performance. These findings have the potential to aid the application of PIM in real systems and contribute to the commercialization of mode transition PIM.

IEEE Transactions on ComputersVol. 74(3)
Seoul National University of Science and Technology (KR), SK Group (South Korea) (KR), Seoul National University (KR)
Openalex Percentile: Top 24%
Parallel Computing and Optimization Techniques
0.98
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.