Many technological concepts of Resistive RAM (RRAM) have been demonstrated in recent years. Simultaneously, a paradigm shift towards integrating computational functions into memory has been observed, with neuromorphic networks as one example.
In this talk, Dr Robin presented where and how RRAM might come in as a potential functional device for developing hardware accelerators for neuromorphic applications. He also discussed the opportunities for using RRAM as a true computational element in an integrated in-memory computing concept. Understanding the dynamic statistical properties of RRAM is the key challenge to unlock the potential of these devices for on-chip artificial intelligence.