Monolithic-3D Integration Augmented Design Techniques for Computing in SRAMs

Srivatsa Rangachar Srinivasa, Wei-Hao Chen, Yung-Ning Tu, Meng-Fan Chang, Jack Sampson, Vijaykrishnan Narayanan

Abstract: In-memory computing has emerged as a promising solution to address the logic-memory performance gap. We propose design techniques using monolithic-3D integration to achieve reliable multirow activation which in turn help in computation as part of data readout. Our design is 1.8x faster than the existing techniques for Boolean computations. We quantitatively show no impact to cell stability when multiple rows are activated and thereby requiring no extra hardware for maintaining the cell stability during computations. In-memory digital to analog conversion technique is proposed using a 3D-CAM primitive. The design utilizes relatively low strength layer-2 transistors effectively and provides 7x power savings when compared with a specialized converter in-memory. Lastly, we present a linear classifier system by making use the above-mentioned techniques which is 47x faster while computing vector matrix multiplication using a dedicated hardware engine.