Energy-/Carbon-Aware Evaluation and Optimization of 3-D IC Architecture With Digital Compute-in-Memory Designs
Several 2-D architectures have been presented, including systolic arrays or compute-in-memory (CIM) arrays for energy-efficient artificial intelligence (AI) inference. To increase the energy efficiency within constrained area, 3-D technologies have been actively investigated, which have the potentia...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Journal on Exploratory Solid-State Computational Devices and Circuits |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10714410/ |
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| Summary: | Several 2-D architectures have been presented, including systolic arrays or compute-in-memory (CIM) arrays for energy-efficient artificial intelligence (AI) inference. To increase the energy efficiency within constrained area, 3-D technologies have been actively investigated, which have the potential to decrease the data path length or increase the activation buffer size, enabling higher energy efficiency. Several works have reported the 3-D architectures using non-CIM designs, but investigations on 3-D architectures with CIM macros have not been well studied in prior works. In this article, we investigate digital CIM (DCIM) macros and various 3-D architectures to find the opportunity of increased energy efficiency compared with 2-D structures. Moreover, we also investigated the carbon footprint of 3-D architectures. We have built in-house simulators calculating energy and area given high-level hardware descriptions and DNN workloads and integrated with carbon estimation tool to analyze the embodied carbon of various hardware designs. We have investigated different types of 3-D DCIM architectures and dataflows, which have shown 42.5% energy savings compared with 2-D systolic arrays on average. Also, we have analyzed the tradeoff between performance and carbon footprint and their optimization opportunities. |
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| ISSN: | 2329-9231 |