# AIDA: Associative DNN Inference Accelerator

arXiv: https://arxiv.org/abs/1901.04976 · HTML: https://mlsanity.com/paper/1901.04976/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Dec 2018.

## Built on by (most cited first, 1 of 1)

- [Vau da muntanialas: Energy-efficient multi-die scalable acceleration of RNN inference](https://mlsanity.com/paper/2202.07462/) (2022)

## Abstract (arXiv)

We propose AIDA, an inference engine for accelerating fully-connected (FC) layers of Deep Neural Network (DNN). AIDA is an associative in-memory processor, where the bulk of data never leaves the confines of the memory arrays, and processing is performed in-situ. AIDA area and energy efficiency strongly benefit from sparsity and lower arithmetic precision. We show that AIDA outperforms the state of art inference accelerator, EIE, by 14.5x (peak performance) and 2.5x (throughput).