Hielm: Highly Flexible In-Memory Computing Using Stt Mram
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.
Publication Date
2-20-2018
Publication Title
Proceedings of the Asia and South Pacific Design Automation Conference, ASP-DAC
Volume
2018-January
Number of Pages
361-366
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/ASPDAC.2018.8297350
Copyright Status
Unknown
Socpus ID
85045308287 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85045308287
STARS Citation
Parveen, Farhana; He, Zhezhi; Angizi, Shaahin; and Fan, Deliang, "Hielm: Highly Flexible In-Memory Computing Using Stt Mram" (2018). Scopus Export 2015-2019. 10053.
https://stars.library.ucf.edu/scopus2015/10053