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

Hussein Bazzi (1, 2) , Jeremy Postel-Pellerin (3, 1) , Hassen Aziza (3, 1) , Mathieu Moreau (3, 1) , Adnan Harb (2)

1 AMU - Aix Marseille Université
2 LIU - Lebanese International University
3 IM2NP - Institut des Matériaux, de Microélectronique et des Nanosciences de Provence

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 based 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.

Mots clés: Resistive memories; Resistive RAM (RRAM); Random Number Generator (RNG); Stochastic switching; Memory array

Domaines: Micro et nanotechnologies/Microélectronique

Hussein Bazzi, Jeremy Postel-Pellerin, Hassen Aziza, Mathieu Moreau, Adnan Harb. Resistive RAM SET and RESET Switching Voltage Evaluation as an Entropy Source for Random Number Generation. 2020 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT), Oct 2020, Frascati, Italy. pp.1-4, ⟨10.1109/DFT50435.2020.9250726⟩. ⟨hal-03504288⟩