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Power Management of Monolithic 3D Manycore Chips with Inter-tier Process Variations

Authors:

Anwesha Chatterjee,

Shouvik Musavvir,

Janardhan Rao Doppa,

Partha Pratim PandeAuthors Info & Claims

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

Article No.: 13, Pages 1 - 19

https://doi.org/10.1145/3430765

Published: 06 January 2021 Publication History

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Abstract

Voltage/frequency island (VFI)-based power management is a popular methodology for designing energy-efficient manycore architectures without incurring significant performance overhead. However, monolithic 3D (M3D) integration has emerged as an enabling technology to design high-performance and energy-efficient circuits and systems. The smaller dimension of vertical monolithic inter-tier vias (MIVs) lowers effective wirelength and allows high integration density. However, sequential fabrication of M3D layers introduces inter-tier process variations that affect the performance of transistors and interconnects in different layers. Therefore, VFI-based power management in M3D manycore systems requires the consideration of inter-tier process variation effects. In this work, we present the design of an imitation learning (IL)-enabled VFI-based power-management strategy that considers the inter-tier process-variation effects in M3D manycore chips. We demonstrate that the IL-based power-management strategy can be fine-tuned based on the M3D characteristics. Our policy generates suitable V/F levels based on the computation and communication characteristics of the system for both process-oblivious and process-aware configurations. We show that the proposed process-variation-aware IL-based VFI implementation for M3D manycore chips lowers the overall energy-delay-product (EDP) by up to 16.2% on average compared to an ideal M3D system with no M3D process variations.

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Cited By

Narang GDeshwal AAyoub RKishinevsky MRao Doppa JPande P(2023)Dynamic Power Management in Large Manycore Systems: A Learning-to-Search FrameworkACM Transactions on Design Automation of Electronic Systems10.1145/360350128:5(1-21)Online publication date: 6-Jun-2023
https://dl.acm.org/doi/10.1145/3603501
Do CKim CChung S(2023)Aggressive GPU cache bypassing with monolithic 3D-based NoCThe Journal of Supercomputing10.1007/s11227-022-04878-679:5(5421-5442)Online publication date: 1-Mar-2023
https://dl.acm.org/doi/10.1007/s11227-022-04878-6
Mirzaei MMohammadi S(2021)Low-power and variation-aware approximate arithmetic units for Image Processing ApplicationsAEU - International Journal of Electronics and Communications10.1016/j.aeue.2021.153825138(153825)Online publication date: Aug-2021
https://doi.org/10.1016/j.aeue.2021.153825

Index Terms

Power Management of Monolithic 3D Manycore Chips with Inter-tier Process Variations

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Published In

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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Publication History

Published: 06 January 2021

Accepted: 01 October 2020

Revised: 01 August 2020

Received: 01 May 2020

Published in JETC Volume 17, Issue 2

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Cited By

Narang GDeshwal AAyoub RKishinevsky MRao Doppa JPande P(2023)Dynamic Power Management in Large Manycore Systems: A Learning-to-Search FrameworkACM Transactions on Design Automation of Electronic Systems10.1145/360350128:5(1-21)Online publication date: 6-Jun-2023
https://dl.acm.org/doi/10.1145/3603501
Do CKim CChung S(2023)Aggressive GPU cache bypassing with monolithic 3D-based NoCThe Journal of Supercomputing10.1007/s11227-022-04878-679:5(5421-5442)Online publication date: 1-Mar-2023
https://dl.acm.org/doi/10.1007/s11227-022-04878-6
Mirzaei MMohammadi S(2021)Low-power and variation-aware approximate arithmetic units for Image Processing ApplicationsAEU - International Journal of Electronics and Communications10.1016/j.aeue.2021.153825138(153825)Online publication date: Aug-2021
https://doi.org/10.1016/j.aeue.2021.153825

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