HielM: Highly flexible in-memory computing using STT MRAM

Farhana Parveen, Zhezhi He, Shaahin Angizi, Deliang Fan

Abstract: In this paper we propose a Highly Flexible InMemory (HieIM) computing platform using STT MRAM, which can be leveraged to implement Boolean logic functions without sacrificing memory functionality. It could pre-process data within memory to further reduce power hungry long distance communication between memory and processing units as in Von-Neumann computing system. HieIM can implement all the Boolean logic functions (AND/NAND, OR/NOR, XOR/XNOR) between any two cells in the same memory array, thus overcoming the `operand locality' problem in contemporary in-memory computing platform designs. To investigate the performance of HieIM, we test in-memory bulk bit-wise Boolean logic operations using different vector datasets, which shows ~ 8x energy saving and ~ 5x speedup compared to recent DRAM based in-memory computing platform. We further implement an in-memory data encryption engine design based on HieIM as another case study. With AES algorithm, it shows 51.5% and 68.9% lower energy consumption compared to CMOS-ASIC and CMOL based implementations, respectively.