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 HfO 2 -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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
