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arXiv · 2505.22868

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

Md Hasibul Amin·Mohammadreza Mohammadi·Jason D. Bakos·Ramtin Zand
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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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Md Hasibul Amin, Mohammadreza Mohammadi, Jason D. Bakos, Ramtin Zand. 2025-05-28. CrossNAS: A Cross-Layer Neural Architecture Search Framework for PIM Systems. https://doi.org/10.1145/3716368.3735178

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