CrossNAS: A Cross-Layer Neural Architecture Search Framework for PIM Systems

Md Hasibul Amin, Mohammadreza Mohammadi, Jason D. Bakos, Ramtin Zand
5/28/2025
cs.ETcs.ARcs.LG

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Abstract

In this paper, we propose the CrossNAS framework, an automated approach for exploring a vast, multidimensional search space that spans various design abstraction layers-circuits, architecture, and systems-to optimize the deployment of machine learning workloads on analog processing-in-memory (PIM) systems. CrossNAS leverages the single-path one-shot weight-sharing strategy combined with the evolutionary search for the first time in the context of PIM system mapping and optimization. CrossNAS sets a new benchmark for PIM neural architecture search (NAS), outperforming previous methods in both accuracy and energy efficiency while maintaining comparable or shorter search times.

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Cite this paper

@article{amin2025crossnas,
  title  = {CrossNAS: A Cross-Layer Neural Architecture Search Framework for PIM Systems},
  author = {Md Hasibul Amin and Mohammadreza Mohammadi and Jason D. Bakos and Ramtin Zand},
  year   = {2025},
  eprint = {2505.22868},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2505.22868v1}
}

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