A Review of Near-Memory Computing Architectures: Opportunities and Challenges
The conventional approach of moving stored data to the CPU for computation has become a major performance bottleneck for emerging scale-out data-intensive applications due to their limited data reuse. At the same time, the advancement in integration technologies have made the decade-old concept of coupling compute units close to the memory (called Near-Memory Computing) more viable. Processing right at the “home” of data can completely diminish the data movement problem of data-intensive applications.
This paper focuses on analyzing and organizing the extensive body of literature on near-memory computing across various dimensions: starting from the memory level where this paradigm is applied, to the granularity of the application that could be executed on the near-memory units. We highlight the challenges as well as the critical need of evaluation methodologies that can be employed in designing these special architectures. Using a case study, we present our methodology and also identify topics for future research to unlock the full potential of near-memory computing.
- A Review of Near-Memory Computing Architectures: Opportunities and Challenges
G. Singh, L. Chelini, S. Corda, A. Javed Awan, S. Stuijk, R. Jordans, H. Corporaal, A. Boonstra.
In Digital System Design, 21st Euromicro Conference, DSD 18 Proceedings, pages xyz-xyz. Prague, Czech Republic, 29 - 31 August 2018. IEEE Computer Society Press, Los Alamitos, CA, USA, 2018. (abstract, pdf, doi).