Ternary Content-Addressable Memory Based on a Single Two-Dimensional Transistor for Memory-Augmented LearningClick to copy article linkArticle link copied!
- Jun CaiJun CaiElmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana 47907, United StatesBirck Nanotechnology Center, Purdue University, West Lafayette, Indiana 47907, United StatesMore by Jun Cai
- Peng Wu*Peng Wu*Email: [email protected]Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United StatesDepartment of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United StatesMore by Peng Wu
- Rahul TripathiRahul TripathiElmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana 47907, United StatesBirck Nanotechnology Center, Purdue University, West Lafayette, Indiana 47907, United StatesMore by Rahul Tripathi
- Jing KongJing KongResearch Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United StatesDepartment of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United StatesMore by Jing Kong
- Zhihong ChenZhihong ChenElmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana 47907, United StatesBirck Nanotechnology Center, Purdue University, West Lafayette, Indiana 47907, United StatesMore by Zhihong Chen
- Joerg Appenzeller*Joerg Appenzeller*Email: [email protected]Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana 47907, United StatesBirck Nanotechnology Center, Purdue University, West Lafayette, Indiana 47907, United StatesMore by Joerg Appenzeller
Abstract
Ternary content-addressable memory (TCAM) is promising for data-intensive artificial intelligence applications due to its large-scale parallel in-memory computing capabilities. However, it is still challenging to build a reliable TCAM cell from a single circuit component. Here, we demonstrate a single transistor TCAM based on a floating-gate two-dimensional (2D) ambipolar MoTe2 field-effect transistor with graphene contacts. Our bottom graphene contacts scheme enables gate modulation of the contact Schottky barrier heights, facilitating carrier injection for both electrons and holes. The 2D nature of our channel and contact materials provides device scaling potentials beyond silicon. By integration with a floating-gate stack, a highly reliable nonvolatile memory is achieved. Our TCAM cell exhibits a resistance ratio larger than 1000 and symmetrical complementary states, allowing the implementation of large-scale TCAM arrays. Finally, we show through circuit simulations that in-memory Hamming distance computation is readily achievable based on our TCAM with array sizes up to 128 cells.
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