OxRAM RNG Circuits Exploiting Multiple Undesirable Nanoscale Phenomena

Abstract

Compact, low-power random number generators (RNG) are essential for applications such as stochastic-, bioinspired-computing, data-encryption, cryptography in communication and security systems. We demonstrate two highly scalable hybrid CMOS-OxRAM RNG implementations based on single OxRAM and 2-OxRAM -circuits. We show how multiple undesirable nanoscale OxRAM phenomena, such as reset-current fluctuation, random telegraph noise (RTN), and reset-state resistance variability in HfOX devices can be coupled to realize RNGs. We show that mitigation of history (memory) effect in 2-OxRAM RNGs can be achieved by using optional OxRAM switching and smaller sampling frequency. Using circuit simulations with calibrated compact models, the proposed hybrid RNG circuits have been validated for 10 nm thick HfO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</sub> devices and 180 nm CMOS node. RNG performance is characterized using chi-square test, serial spectral test, and covariance/correlation-based analysis.