SK hynix, TetraMem, and researchers from the University of Southern California have developed a memristor-based in-memory computing (IMC) system-on-chip (SoC) for AI edge devices. The device is designed to accelerate neural network inference in lightweight AI models while consuming a fraction of the power that higher-end GPUs or NPUs would. To a large degree, the SoC is a proof-of-concept chip, as its performance would peak at around 2.54 TOPS in a theoretical best-case scenario, which is 16X below Microsoft's Copilot+ requirements.
