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Scalability Limitations of Processing-in-Memory using Real System Evaluations

Published: 10 June 2024 Publication History

Abstract

Processing-in-memory (PIM) has been widely explored in academia and industry to accelerate numerous workloads. By reducing the data movement and increasing parallelism, PIM offers great performance and energy efficiency. A large amount of cores or nodes present in PIM provide massive parallelism and compute throughput; however, this also proposes challenges and limitations for some workloads. In this work, we provide an extensive evaluation and analysis of a real PIM system from UPMEM. We specifically target emerging workloads featuring collective communication, demonstrating its role as the primary limitation within current PIM architecture.

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Yongkee Kwon, Guhyun Kim, Nahsung Kim, et al. 2023. Memory-Centric Computing with SK Hynix's Domain-Specific Memory. In 2023 IEEE Hot Chips 35 Symposium (HCS). 1--26. https://doi.org/10.1109/HCS59251.2023.10254717
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Young-Cheon Kwon, Suk Han Lee, Jaehoon Lee, et al. 2021. 25.4 A 20nm 6GB Function-In-Memory DRAM, Based on HBM2 with a 1.2TFLOPS Programmable Computing Unit Using Bank-Level Parallelism, for Machine Learning Applications. In 2021 IEEE International Solid-State Circuits Conference (ISSCC), Vol. 64. 350--352. https://doi.org/10.1109/ISSCC42613.2021.9365862
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  1. Scalability Limitations of Processing-in-Memory using Real System Evaluations

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    cover image ACM Conferences
    SIGMETRICS/PERFORMANCE '24: Abstracts of the 2024 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems
    June 2024
    120 pages
    ISBN:9798400706240
    DOI:10.1145/3652963
    • cover image ACM SIGMETRICS Performance Evaluation Review
      ACM SIGMETRICS Performance Evaluation Review  Volume 52, Issue 1
      SIGMETRICS '24
      June 2024
      104 pages
      DOI:10.1145/3673660
      • Editor:
      • Bo Ji
      Issue’s Table of Contents
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    New York, NY, United States

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    Published: 10 June 2024

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    Author Tags

    1. collective communication
    2. interconnection networks
    3. processing-in-memory

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