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Monolithic 3D+-IC based massively parallel compute-in-memory macro for accelerating database and machine learning primitives
Conference paper

Monolithic 3D+-IC based massively parallel compute-in-memory macro for accelerating database and machine learning primitives

Akshay Krishna Ramanathan, Srivatsa Srinivasa Rangachar, Je-Min Hung, Chun-Ying Lee, Cheng-Xin Xue, Sheng-Po Huang, Fu-Kuo Hsueh, Jia-Min Shieh, Wen-Kuan Yeh, Mon-Shu Ho, …
Technical Digest - International Electron Devices Meeting, IEDM, Vol.2020-December, pp.28.5.1-28.5.4
12/2020
DOI: https://doi.org/10.1109/IEDM13553.2020.9372111
Appears in  keyword about Physics

Abstract

Electronic Optical and Magnetic Materials Condensed Matter Physics Electrical and Electronic Engineering Materials Chemistry
This paper demonstrates the first Monolithic 3D+-IC based Compute-in-Memory (CiM) Macro performing massively parallel beyond-Boolean operations targeting database and machine learning (ML) applications. The proposed CiM technique supports data filtering, sorting, and sparse matrix-matrix multiplication (SpGEMM) operations. Our system exhibits up to 272x speedup and 151x energy savings compared to the ASIC baseline.

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