# Near-Memory Computing: Past, Present, and Future

## TL;DR

This paper surveys the evolution, current state, and future prospects of near-memory computing (NMC), emphasizing its potential to reduce data movement bottlenecks in data-intensive applications.

## Contribution

It provides a comprehensive survey of NMC technologies, identifies key challenges, and introduces a new approach including microarchitecture-independent characterization, a compiler framework, and an analytical model.

## Key findings

- NMC can significantly reduce data movement in data-intensive applications.
- The paper identifies critical challenges and open issues in NMC development.
- Proposes a novel framework for NMC application characterization and evaluation.

## Abstract

The conventional approach of moving data to the CPU for computation has become a significant performance bottleneck for emerging scale-out data-intensive applications due to their limited data reuse. At the same time, the advancement in 3D integration technologies has made the decade-old concept of coupling compute units close to the memory --- called near-memory computing (NMC) --- more viable. Processing right at the "home" of data can significantly diminish the data movement problem of data-intensive applications. In this paper, we survey the prior art on NMC across various dimensions (architecture, applications, tools, etc.) and identify the key challenges and open issues with future research directions. We also provide a glimpse of our approach to near-memory computing that includes i) NMC specific microarchitecture independent application characterization ii) a compiler framework to offload the NMC kernels on our target NMC platform and iii) an analytical model to evaluate the potential of NMC.