Resources

Discussing Weebit ReRAM endurance performance and what it means for embedded memory applications

A simple overview of how customers integrate Weebit ReRAM into their SoCs through standard semiconductor design flows

How ReRAM can help reduce data movement and power consumption in datacenter workloads, helping solve a major issue in AI systems

Why customers are evaluating and adopting Weebit ReRAM as a next-generation embedded NVM for advanced semiconductor designs

How ReRAM can support new AI architectures, including in-memory compute and neuromorphic computing, by bringing memory closer to processing

Exploring the NVM options for Edge AI and why ReRAM is well suited to low-power, data-intensive embedded applications

A short discussion on how memory architecture affects power consumption, and why low-power NVM matters for future SoCs

Explaining how Weebit ReRAM scales across process nodes and why this matters for advanced embedded designs

Technical progress update from embedded world 2026, including qualification, yield improvement, endurance data and roadmap direction (EW26)

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)

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