Work

Resistive RAM SET and RESET Switching Voltage Evaluation as an Entropy Source for Random Number Generation

Year: 2020

Type: conference-paper

Abstract: The intrinsic variability of the switching parameters in resistive memories has been a major wall that limits their adoption as the next generation memories. In contrast, this natural stochasticity can be beneficial for other applications such as Random Number Generators (RNGs). This paper presents two RNG approaches relying on a 130nm HfO2-based Resistive RAM (RRAM) memory array. The memory array is programmed with a voltage close to the median value of the SET (resp. RESET) voltage distribution to benefit from the SET (resp. RESET) voltage variability. In both cases, only a subset of the memory array is programmed, resulting in a stochastic distribution of cell resistance values. Resistance values are next converted into a bit stream and confronted to National Institute of Standards and Technology (NIST) test benchmarks.

Source: IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT)

DOI: 10.1109/dft50435.2020.9250726

Authors: Hussein Bazzi, Jeremy Postel-Pellerin, Hassen Aziza, Mathieu Moreau, Adnan Harb

Institutions: Aix-Marseille Université, Lebanese International University, Institut des Matériaux, de Microélectronique et des Nanosciences de Provence, International University of Beirut

Language: English

Topic: Advanced Memory and Neural Computing

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

Funder: Mars

OpenAlex ID: W3100995962

FWCI: 0.363

Cites: 25

Cited by: 1

Related to: 10