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Functional Demonstration of a Memristive Arithmetic Logic Unit (MemALU) for In‐Memory Computing
Author(s) -
Cheng Long,
Li Yi,
Yin KangSheng,
Hu SiYu,
Su YuTing,
Jin MiaoMiao,
Wang ZhuoRui,
Chang TingChang,
Miao XiangShui
Publication year - 2019
Publication title -
advanced functional materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.069
H-Index - 322
eISSN - 1616-3028
pISSN - 1616-301X
DOI - 10.1002/adfm.201905660
Subject(s) - von neumann architecture , computer science , arithmetic logic unit , memristor , arithmetic , adder , multiplication (music) , logic gate , in memory processing , unconventional computing , computer hardware , parallel computing , computer architecture , electronic engineering , mathematics , algorithm , telecommunications , combinatorics , information retrieval , search engine , latency (audio) , query by example , engineering , web search query , operating system
Abstract The development of in‐memory computing has opened up possibilities to build next‐generation non‐von‐Neumann computing architecture. Implementation of logic functions within the memristors can significantly improve the energy efficiency and alleviate the bandwidth congestion issue. In this work, the demonstration of arithmetic logic unit functions is presented in a memristive crossbar with implemented non‐volatile Boolean logic and arithmetic computing. For logic implementation, a standard operating voltage mode is proposed for executing reconfigurable stateful IMP, destructive OR, NOR, and non‐destructive OR logic on both the word and bit lines. No additional voltages are needed beyond “ V P ” and its negative component. With these basic logic functions, other Boolean functions are constructed within five devices in at most five steps. For arithmetic computing, the fundamental functions including an n ‐bit full adder with high parallelism as well as efficient increment, decrement, and shift operations are demonstrated. Other arithmetic blocks, such as subtraction, multiplication, and division are further designed. This work provides solid evidence that memristors can be used as the building block for in‐memory computing, targeting various low‐power edge computing applications.