@inproceedings{43aacb98fe064a4d8782a46c5547ab7f,
title = "High-throughput PIM (Processing in-Memory) for DRAM using Bank-level Pipelined Architecture",
abstract = "Artificial intelligence (AI) is a technology requires massive computation. Among many solutions that accelerate AI for faster computation and low power, processing-in-memory (PIM) is a promising candidate. In this paper, we propose a PIM architecture of DRAM via custom pipelining. Our architecture proposes pipelining of operation units that leads to massive throughput, where an operation unit consists of eight banks. Our optimized pipelined architecture shows a -19.16% reduction in power-delay-product (PDP) per area and 24.1% better throughput compared to the latest DRAM PIM architecture with only 0.7% area overhead.",
keywords = "DRAM, Pipelining, processing in-memory (PIM)",
author = "Hyunsoo Lee and Hyundong Lee and Minseung Shin and Gyuri Shin and Sumin Jeon and Taigon Song",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 20th International SoC Design Conference, ISOCC 2023 ; Conference date: 25-10-2023 Through 28-10-2023",
year = "2023",
doi = "10.1109/ISOCC59558.2023.10396302",
language = "English",
series = "Proceedings - International SoC Design Conference 2023, ISOCC 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "101--102",
booktitle = "Proceedings - International SoC Design Conference 2023, ISOCC 2023",
address = "United States",
}