research-article

CLU: A Near-Memory Accelerator Exploiting the Parallelism in Convolutional Neural Networks

Authors:

Hemangee K. KapoorAuthors Info & Claims

ACM Journal on Emerging Technologies in Computing Systems (JETC), Volume 17, Issue 2

Article No.: 22, Pages 1 - 25

https://doi.org/10.1145/3427472

Published: 15 April 2021 Publication History

Abstract

Convolutional/Deep Neural Networks (CNNs/DNNs) are rapidly growing workloads for the emerging AI-based systems. The gap between the processing speed and the memory-access latency in multi-core systems affects the performance and energy efficiency of the CNN/DNN tasks. This article aims to alleviate this gap by providing a simple and yet efficient near-memory accelerator-based system that expedites the CNN inference. Towards this goal, we first design an efficient parallel algorithm to accelerate CNN/DNN tasks. The data is partitioned across the multiple memory channels (vaults) to assist in the execution of the parallel algorithm. Second, we design a hardware unit, namely the convolutional logic unit (CLU), which implements the parallel algorithm. To optimize the inference, the CLU is designed, and it works in three phases for layer-wise processing of data. Last, to harness the benefits of near-memory processing (NMP), we integrate homogeneous CLUs on the logic layer of the 3D memory, specifically the Hybrid Memory Cube (HMC). The combined effect of these results in a high-performing and energy-efficient system for CNNs/DNNs. The proposed system achieves a substantial gain in the performance and energy reduction compared to multi-core CPU- and GPU-based systems with a minimal area overhead of 2.37%.

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Cited By

Wang JDu HDing BXu QChen SKang Y(2023)DDAM: Data Distribution-Aware Mapping of CNNs on Processing-In-Memory SystemsACM Transactions on Design Automation of Electronic Systems10.1145/357619628:3(1-30)Online publication date: 19-Mar-2023
https://dl.acm.org/doi/10.1145/3576196
An JAliaj EJun S(2023)PreCog: Near-Storage Accelerator for Heterogeneous CNN Inference2023 IEEE 34th International Conference on Application-specific Systems, Architectures and Processors (ASAP)10.1109/ASAP57973.2023.00021(45-52)Online publication date: Jul-2023
https://doi.org/10.1109/ASAP57973.2023.00021
Thomas K APoddar SMondal H(2022)A CNN Hardware Accelerator Using Triangle-based ConvolutionACM Journal on Emerging Technologies in Computing Systems10.1145/354497518:4(1-23)Online publication date: 13-Oct-2022
https://dl.acm.org/doi/10.1145/3544975
Show More Cited By

Index Terms

CLU: A Near-Memory Accelerator Exploiting the Parallelism in Convolutional Neural Networks
1. Computer systems organization
  1. Architectures
    1. Other architectures
      1. Neural networks
2. Hardware
  1. Very large scale integration design
    1. Application-specific VLSI designs
      1. Application specific integrated circuits

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cover image ACM Journal on Emerging Technologies in Computing Systems

ACM Journal on Emerging Technologies in Computing Systems Volume 17, Issue 2

Hardware and Algorithms for Efficient Machine Learning

April 2021

360 pages

ISSN:1550-4832

EISSN:1550-4840

DOI:10.1145/3446841

Editor:
Ramesh Karri
Polytechnic Institute of New York University, USA

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ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 15 April 2021

Accepted: 01 September 2020

Revised: 01 August 2020

Received: 01 May 2020

Published in JETC Volume 17, Issue 2

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Cited By

Wang JDu HDing BXu QChen SKang Y(2023)DDAM: Data Distribution-Aware Mapping of CNNs on Processing-In-Memory SystemsACM Transactions on Design Automation of Electronic Systems10.1145/357619628:3(1-30)Online publication date: 19-Mar-2023
https://dl.acm.org/doi/10.1145/3576196
An JAliaj EJun S(2023)PreCog: Near-Storage Accelerator for Heterogeneous CNN Inference2023 IEEE 34th International Conference on Application-specific Systems, Architectures and Processors (ASAP)10.1109/ASAP57973.2023.00021(45-52)Online publication date: Jul-2023
https://doi.org/10.1109/ASAP57973.2023.00021
Thomas K APoddar SMondal H(2022)A CNN Hardware Accelerator Using Triangle-based ConvolutionACM Journal on Emerging Technologies in Computing Systems10.1145/354497518:4(1-23)Online publication date: 13-Oct-2022
https://dl.acm.org/doi/10.1145/3544975
Tao GLi YXu YFan JShen HHuang K(2022)A Near Memory Computing FPGA Architecture for Neural Network Acceleration2022 2nd International Conference on Frontiers of Electronics, Information and Computation Technologies (ICFEICT)10.1109/ICFEICT57213.2022.00100(543-548)Online publication date: Aug-2022
https://doi.org/10.1109/ICFEICT57213.2022.00100

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