Pathfinding Future PIM Architectures by Demystifying a Commercial PIM Technology
Bongjoon Hyun, Taehun Kim, Dongjae Lee, Minsoo Rhu
摘要
Processing-in-memory (PIM) has been explored for decades by computer architects, yet it has never seen the light of day in real-world products due to its high design overheads and lack of a killer application. With the advent of critical memoryintensive workloads, several commercial PIM technologies have been introduced to the market, ranging from domain-specific PIM architectures to more general-purpose PIM architectures. In this work, we deepdive into UPMEM's commercial PIM technology, a general-purpose PIM-enabled parallel computing architecture that is highly programmable. Our first key contribution is the development of a flexible simulation framework for PIM. The simulator we developed (aka uPIMulator) enables the compilation of UPMEM-PIM source codes into its compiled machine-level instructions, which are subsequently consumed by our cycle-level performance simulator. Using uPIMulator, we demystify UPMEM's PIM design through a detailed characterization study. Finally, we identify some key limitations of the current UPMEM-PIM system through our case studies and present some important architectural features that will become critical for future PIM architectures to support.
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引用它的顶会 Paper21
- NeuPIMs: NPU-PIM Heterogeneous Acceleration for Batched LLM InferencingGuseul Heo, Sangyeop Lee, Jaehong Cho, Hyunmin Choi 等ASPLOS 2024 · 被引用 121 次
- PAPI: Exploiting Dynamic Parallelism in Large Language Model Decoding with a Processing-In-Memory-Enabled Computing SystemYintao He, Haiyu Mao, Christina Giannoula, Mohammad Sadrosadati 等ASPLOS 2025 · 被引用 37 次
- PIM-MMU: A Memory Management Unit for Accelerating Data Transfers in Commercial PIM SystemsDongjae Lee, Bongjoon Hyun, Taehun Kim, Minsoo RhuMICRO 2024 · 被引用 23 次
- PID-Comm: A Fast and Flexible Collective Communication Framework for Commodity Processing-in-DIMM DevicesSi Ung Noh, Junguk Hong, Chaemin Lim, Seongyeon Park 等ISCA 2024 · 被引用 12 次
- UniNDP: A Unified Compilation and Simulation Tool for Near DRAM Processing ArchitecturesTongxin Xie, Zhenhua Zhu, Bing Li, Yukai He 等HPCA 2025 · 被引用 9 次
它引用的顶会 Paper25
- RecNMP: Accelerating Personalized Recommendation with Near-Memory ProcessingLiu Ke, Udit Gupta, Benjamin Youngjae Cho, David Brooks 等ISCA 2020 · 被引用 235 次
- Newton: A DRAM-maker's Accelerator-in-Memory (AiM) Architecture for Machine LearningMingxuan He, Choungki Song, Ilkon Kim, Chunseok Jeong 等MICRO 2020 · 被引用 208 次
- SIMDRAM: a framework for bit-serial SIMD processing using DRAMNastaran Hajinazar, Geraldo F. Oliveira, Sven Gregorio, João Dinis Ferreira 等ASPLOS 2021 · 被引用 182 次
- AccelWattch: A Power Modeling Framework for Modern GPUsVijay Kandiah, Scott Peverelle, Mahmoud Khairy, Junrui Pan 等MICRO 2021 · 被引用 134 次
- SpaceA: Sparse Matrix Vector Multiplication on Processing-in-Memory AcceleratorXinfeng Xie, Zheng Liang, Peng Gu, Abanti Basak 等HPCA 2021 · 被引用 111 次
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