Exploring Specialized Near-Memory Processing for Data Intensive Operations

被引:0
|
作者
Yitbarek, Salessawi Ferede [1 ]
Yang, Tao [2 ]
Das, Reetuparna [1 ]
Austin, Todd [1 ]
机构
[1] Univ Michigan, Ann Arbor, MI 48109 USA
[2] Univ Calif San Diego, San Diego, CA 92103 USA
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Emerging 3D stacked memory systems provide significantly more bandwidth than current DDR modules. However, general purpose processors do not take full advantage of these resources offered by the memory modules. Taking advantage of the increased bandwidth requires the use of specialized processing units. In this paper, we evaluate the benefits of placing hardware accelerators at the bottom layer of a 3D stacked memory system compared to accelerators that are placed external to the memory stack. Our evaluation of the design using cycle-accurate simulation and RTL synthesis shows that, for important data intensive kernels, near-memory accelerators inside a single 3D memory package provide 3x-13x speedup over a Quad-core Xeon processor. Most of the benefits are from the application of accelerators, as the near-memory configurations provide marginal benefits compared to the same number of accelerators placed on a die external to the memory package. This comparable performance for external accelerators is due to the high bandwidth afforded by the high-speed off-chip links. On the other hand, near-memory accelerators consume 7%-39% less energy than the external accelerators.
引用
收藏
页码:1449 / 1452
页数:4
相关论文
共 50 条
  • [21] PLANAR: A Programmable Accelerator for Near-Memory Data Rearrangement
    Barredo, Adrian
    Armejach, Adria
    Beard, Jonathan C.
    Moreto, Miquel
    PROCEEDINGS OF THE 2021 ACM INTERNATIONAL CONFERENCE ON SUPERCOMPUTING, ICS 2021, 2021, : 164 - 176
  • [22] Algorithm/Architecture Co-Design for Near-Memory Processing
    Drumond M.
    Daglis A.
    Mirzadeh N.
    Ustiugov D.
    Picorel J.
    Falsafi B.
    Grot B.
    Pnevmatikatos D.
    2018, Association for Computing Machinery (52): : 109 - 122
  • [23] Near-Memory Address Translation
    Picorel, Javier
    Jevdjic, Djordje
    Falsafi, Babak
    2017 26TH INTERNATIONAL CONFERENCE ON PARALLEL ARCHITECTURES AND COMPILATION TECHNIQUES (PACT), 2017, : 303 - 317
  • [24] Accelerating Personalized Recommendation with Cross-level Near-Memory Processing
    Liu, Haifeng
    Zheng, Long
    Huang, Yu
    Liu, Chaoqiang
    Ye, Xiangyu
    Yuan, Jingrui
    Liao, Xiaofei
    Jin, Hai
    Xue, Jingling
    PROCEEDINGS OF THE 2023 THE 50TH ANNUAL INTERNATIONAL SYMPOSIUM ON COMPUTER ARCHITECTURE, ISCA 2023, 2023, : 924 - 936
  • [25] Exploiting Near-Memory Processing Architectures for Bayesian Neural Networks Acceleration
    Zhao, Yinglin
    Yang, Jianlei
    Jia, Xiaotao
    Wang, Xueyan
    Wang, Zhaohao
    Kang, Wang
    Zhang, Youguang
    Zhao, Weisheng
    2019 IEEE COMPUTER SOCIETY ANNUAL SYMPOSIUM ON VLSI (ISVLSI 2019), 2019, : 204 - 207
  • [26] SuperCut: Communication-Aware Partitioning for Near-Memory Graph Processing
    Zhao, Chenfeng
    Chamberlain, Roger D.
    Zhang, Xuan
    PROCEEDINGS OF THE 20TH ACM INTERNATIONAL CONFERENCE ON COMPUTING FRONTIERS 2023, CF 2023, 2023, : 42 - 51
  • [27] Towards Accelerating k-NN with MPI and Near-Memory Processing
    Ahn, Hooyoung
    Kim, Seonyoung
    Park, Yoomi
    Han, Woojong
    Contini, Nick
    Ramesh, Bharath
    Abduljabbar, Mustafa
    Panda, Dhabaleswar K.
    2024 IEEE INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM WORKSHOPS, IPDPSW 2024, 2024, : 608 - 615
  • [28] FeFETs for Near-Memory and In-Memory Compute
    Salahuddin, Saveef
    Tan, Ava
    Cheema, Suraj
    Shanker, Nirmaan
    Hoffmann, Michael
    Bae, J-H
    2021 IEEE INTERNATIONAL ELECTRON DEVICES MEETING (IEDM), 2021,
  • [29] Triple Engine Processor (TEP): A Heterogeneous Near-Memory Processor for Diverse Kernel Operations
    Lim, Hongyeol
    Park, Giho
    ACM TRANSACTIONS ON ARCHITECTURE AND CODE OPTIMIZATION, 2017, 14 (04)
  • [30] Near-Memory Acceleration for Radio Astronomy
    Fiorin, Leandro
    Jongerius, Rik
    Vermij, Erik
    van Lunteren, Jan
    Hagleitner, Christoph
    IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2018, 29 (01) : 115 - 128