CiM3D: Comparator-in-Memory Designs Using Monolithic 3-D Technology for Accelerating Data-Intensive Applications

Abstract

The compare operation is widely used in many applications, from fundamental sorting to primitive operations in the database and AI systems. We present SRAM-based 3-D-CAM circuit designs using a monolithic 3-D (M3D) integration process for realizing beyond-Boolean in-memory compare operation without any area overheads. We also fabricated a processing-in-memory (PiM) macro with the same 3-D-CAM circuit using M3D for performing massively parallel compare operations used in the database, machine learning, and scientific applications. We show various system designs with the 3-D-CAM supporting operations, such as data filtering, sorting, and sparse matrix–matrix multiplication (SpGEMM). Our systems exhibit up to $272\times $ , $200\times $ , and $226\times $ speedups and $151\times $ , $37\times $ , and $156\times $ energy savings compared to systems using near memory compute for the data filtering, sorting, and SpGEMM applications, respectively.

Keywords

• 3-D-SRAM
• computing-in-memory
• monolithic (sequential) 3-D integrated circuit (M3D-IC)
• sparse matrix multiplication