Low-Overhead General-Purpose Near-Data Processing in CXL Memory Expanders
The paper presents a low-overhead general-purpose near-data processing architecture for CXL memory, named Memory-Mapped NDP (M^2NDP). This architecture aims to enhance performance for memory-bound applications by reducing latency and energy consumption. The proposed solution achieves significant speedups and energy savings compared to traditional CPU/GPU systems.
- ▪CXL enables cost-efficient memory expansion beyond local DRAM, but frequent memory accesses can slow down applications.
- ▪The proposed M^2NDP architecture includes memory-mapped functions and lightweight μthreads for efficient processing.
- ▪M^2NDP can achieve speedups of up to 128x and energy reductions of up to 87.9% compared to baseline systems.
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| Original publisher | arXiv.org |
| Canonical URL | https://arxiv.org/abs/2404.19381 |
| Publication time | Sat, 23 May 2026 20:52:46 +0000 |
| Retrieval time | 2026-05-23T21:07:27.737Z |
| Last seen | 2026-05-23T21:07:27.737Z |
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Computer Science > Hardware Architecture arXiv:2404.19381 (cs) [Submitted on 30 Apr 2024 (v1), last revised 23 Sep 2024 (this version, v3)] Title:Low-overhead General-purpose Near-Data Processing in CXL Memory Expanders Authors:Hyungkyu Ham, Jeongmin Hong, Geonwoo Park, Yunseon Shin, Okkyun Woo, Wonhyuk Yang, Jinhoon Bae, Eunhyeok Park, Hyojin Sung, Euicheol Lim, Gwangsun Kim View a PDF of the paper titled Low-overhead General-purpose Near-Data Processing in CXL Memory Expanders, by Hyungkyu Ham and 10 other authors View PDF HTML (experimental) Abstract:Emerging Compute Express Link (CXL) enables cost-efficient memory expansion beyond the local DRAM of processors.
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