4.3 Article

Monolithic 3D stacked multiply-accumulate units

期刊

INTEGRATION-THE VLSI JOURNAL
卷 76, 期 -, 页码 183-189

出版社

ELSEVIER
DOI: 10.1016/j.vlsi.2020.10.006

关键词

Multiply-accumulate; M3D stacking; TSV-Based 3D stacking; ASIC

资金

  1. National Research Foundation of Korea (NRF), South Korea - Korea government (MSIT) [2017R1A2B2002930, 2020R1A2C2003500]
  2. Nano Material Technology Development Program through the National Research Foundation of Korea (NRF), South Korea - Ministry of Science, ICT & Future Planning (MSIP) [2015M3A7B7045470, 2016M3A7B4910430]
  3. Samsung Electronics, South Korea
  4. Korea University, South Korea
  5. National Research Foundation of Korea [2016M3A7B4910430, 2017R1A2B2002930, 2020R1A2C2003500] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

向作者/读者索取更多资源

The M3D stacking technology reduces critical path delay, dynamic energy, and leakage power compared to conventional 2D structures and TSV stacked units, making it a more efficient option for MAC units in applications like convolutional neural networks. The peak temperature of M3D stacking is also shown to be lower than that of TSV-based 3D stacking.
The monolithic 3D stacking (M3D) reduces the critical path delay, leveraging 1) short latency of a monolithic inter-tier via (MIV) and 2) short 2D interconnect and cell delay through smaller footprint. In this paper, we propose M3D stacked multiply-accumulate (MAC) units; MAC units have a relatively large number of long wires. With the Samsung 28 nm ASIC library, the M3D stacked MAC units reduce the critical path delay by up to 28.9%, compared to the conventional 2D structure. In addition, the M3D stacked MAC units reduce dynamic energy and leakage power by up to 9.6% and 21.7%, respectively. Compared to the TSV stacked MAC units, the M3D stacked MAC units consume less dynamic energy and leakage power by up to 37.1% and 73.6%, respectively. Though the 3D stacking technology inevitably causes higher peak temperature than the 2D structure, our thermal results show that the peak temperature of the M3D stacking is always lower than that of the TSV-based 3D stacking. Furthermore, when the size of the MAC unit is optimized in convolutional neural network (CNN) applications, the peak temperature of the M3D stacking is 88.3 degrees C at most, which is still under the threshold temperature.

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