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A Case for 3D Integrated System Design for Neuromorphic Computing & AI Applications

arXiv 2103.04852 ↗First posted 2 Mar 2021cs.ET cs.AI cs.ARcited by 0

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Abstract (arXiv)

Over the last decade, artificial intelligence has found many applications areas in the society. As AI solutions have become more sophistication and the use cases grew, they highlighted the need to address performance and energy efficiency challenges faced during the implementation process. To address these challenges, there has been growing interest in neuromorphic chips. Neuromorphic computing relies on non von Neumann architectures as well as novel devices, circuits and manufacturing technologies to mimic the human brain. Among such technologies, 3D integration is an important enabler for AI hardware and the continuation of the scaling laws. In this paper, we overview the unique opportunities 3D integration provides in neuromorphic chip design, discuss the emerging opportunities in next generation neuromorphic architectures and review the obstacles. Neuromorphic architectures, which relied on the brain for inspiration and emulation purposes, face grand challenges due to the limited understanding of the functionality and the architecture of the human brain. Yet, high-levels of investments are dedicated to develop neuromorphic chips. We argue that 3D integration not only provides strategic advantages to the cost-effective and flexible design of neuromorphic chips, it may provide design flexibility in incorporating advanced capabilities to further benefits the designs in the future.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 4 of its 81 references that are in the map. First posted on arXiv 2 Mar 2021.

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References · 4

  1. 2017A Survey of Neuromorphic Computing and Neural Networks in Hardwarecited by 85
  2. 2017A scalable multi-core architecture with heterogeneous memory structures for Dynamic Neuromorphic Asynchronous Processors (DYNAPs)cited by 52
  3. 2016Fathom: Reference Workloads for Modern Deep Learning Methodscited by 20
  4. 2020Stack up your chips: Betting on 3D integration to augment Moore's Law scalingcited by 1

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