Resources
Watch a simple demo showing how ReRAM can efficiently store weights for AI inference at the edge
Weebit ReRAM is in various engagement stages with commercial fabs for various AI architectures, such as the AEC-Q100 qualification targeting automotive applications (FMS 2025)
Weebit ReRAM is in various engagement stages with commercial fabs for various AI architectures that are being developed for edge applications (FMS 2025)
Why ReRAM is a game changer for AI, discussing near-memory compute, and in-memory compute architectures (LIST Tech Days 2025)
Demonstrating how a ReRAM-based platform can support on-chip customized learning in real-time at the edge (Weebit, CEA-Leti and Université Paris-Saclay; 2025 IEEE Symposium on VLSI Technology and Circuits)
Proposing an optimized programming strategy to mitigate the impact of write termination (WT) on relaxation effects in ReRAM, particularly relevant for neuromorphic and in-memory computing applications (IMW 2025)
An analysis of the memristor industry, focusing on products that are commercially available and prototypes that might affect the market in the near future (Nature, April 2025)
Part of the “Designed with Cadence” series, this blog/video explains why the industry needs new NVM, introduces Weebit ReRAM, and discusses ReRAM design challenges
Why ReRAM is the logical alternative to flash for use in automotive and edge AI, plus future neuromorphic computing applications (Select slides from ICCAD-Expo 2024)
How ReRAM’s physical properties can be controlled and how the device can be operated to align with AI and in-memory computing (IMC) requirements (IEEE SOCC 2024)
A comprehensive assessment of the impact of various design assist techniques on the inherent performance and reliability of native ReRAM on silicon (IEEE Journal of Solid State Circuits)
Why ReRAM is an ideal solution for applications with extended requirements such as automotive, plus initial results of Weebit ReRAM on GlobalFoundries’ 22FDX® wafers (FMS 2024)