# Design Considerations for Efficient Deep Neural Networks on Processing-in-Memory Accelerators

Source: [Design Considerations for Efficient Deep Neural Networks on Processing-in-Memory Accelerators](<https://www.sota2.com/research/paper/68fa66d11e209131cea1298e>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T21:59:21.344Z

Authors: Tien-Ju Yang, Vivienne Sze

Published: 2019-12-18T19:23:29.000Z

## Abstract

This paper describes various design considerations for deep neural networks that enable them to operate efficiently and accurately on processing-in-memory accelerators. We highlight important properties of these accelerators and the resulting design considerations using experiments conducted on various state-of-the-art deep neural networks with the large-scale ImageNet dataset.

## Recorded benchmark results

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## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1912.12167>)

[PDF](<https://arxiv.org/pdf/1912.12167.pdf>)