In Advanced materials (Deerfield Beach, Fla.)
As the energy and hardware investments necessary for conventional high-precision digital computing continues to explode in the emerging era of artificial intelligence, deep learning, and big data, a change in paradigm that can trade precision for energy and resource efficiency is being sought for many computing applications. Stochastic computing (SC) is an attractive alternative since unlike digital computers, which require many logic gates and a high transistor volume to perform basic arithmetic operations such as addition, subtraction, multiplication, sorting, etc., SC can implement the same using simple logic gates. While it is possible to accelerate SC using traditional silicon complementary metal-oxide-semiconductor (CMOS) technology, the need for extensive hardware investment to generate stochastic bits (s-bits), the fundamental computing primitive for SC, makes it less attractive. Memristor and spin-based devices offer natural randomness but depend on hybrid designs involving CMOS peripherals for accelerating SC, which increases area and energy burden. Here, we overcome the limitations of existing and emerging technologies and experimentally demonstrate a standalone SC architecture embedded in memory based on two-dimensional (2D) memtransistors. Our monolithic and non-von Neumann SC architecture consumes a miniscule amount of energy (< 1 nJ) for both s-bit generation and arithmetic operations, and it also occupies a small hardware footprint, highlighting the benefits of SC. This article is protected by copyright. All rights reserved.
Ravichandran Harikrishnan, Zheng Yikai, Schranghamer Thomas F, Trainor Nicholas, Redwing Joan M, Das Saptarshi
2022-Oct-29
2D Materials, Arithmetic, Stochastic computing, memtransistor
