# A Distributed Emulation Environment for In-Memory Computing Systems

arXiv: https://arxiv.org/abs/2510.08257 · HTML: https://mlsanity.com/paper/2510.08257/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 15 references that are in the map.
- First posted on arXiv 9 Oct 2025.

## Builds on (most cited first, 2 of 2)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [End-to-end 100-TOPS/W Inference With Analog In-Memory Computing: Are We There Yet?](https://mlsanity.com/paper/2109.01404/) (2021)

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

- [Performance Analysis of Edge and In-Sensor AI Processors: A Comparative Review](https://mlsanity.com/paper/2603.08725/) (2026)

## Abstract (arXiv)

In-memory computing technology is used extensively in artificial intelligence devices due to lower power consumption and fast calculation of matrix-based functions. The development of such a device and its integration in a system takes a significant amount of time and requires the use of a real-time emulation environment, where various system aspects are analyzed, microcode is tested, and applications are deployed, even before the real chip is available. In this work, we present the architecture, the software development tools, and experimental results of a distributed and expandable emulation system for rapid prototyping of integrated circuits based on in-memory computing technologies. Presented experimental results demonstrate the usefulness of the proposed emulator.