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.
@article{arxiv.1908.02640,
title = {Near-Memory Computing: Past, Present, and Future},
author = {Gagandeep Singh and Lorenzo Chelini and Stefano Corda and Ahsan Javed Awan and Sander Stuijk and Roel Jordans and Henk Corporaal and Albert-Jan Boonstra},
journal= {arXiv preprint arXiv:1908.02640},
year = {2019}
}