Memory Class Storage, and its Impact

Nantero NRAM™ is a new class of memory with the potential to add non-volatility to existing RAM applications. It can be arranged in a crosspoint structure for large memories or a 1T-nR arrangement for smaller faster arrays, in standalone devices or as embedded RAM. NRAM uses carbon nanotubes in a dielectric-free structure to achieve unlimited write endurance. While there are obvious advantages to this class of device, including replacing DRAM in storage devices, there are a number of less obvious changes to how designers approach the data storage hierarchy. Decoupling cache size from battery backup power lets designers rethink performance profiles. Exploitation of various interfaces into the system are examined, from SATA to PCIe to the many options in the DRAM bus. This presentation also explores the growing application space for artificial intelligence, deep learning, and in-memory computing and considers the impact of a high performance non-volatile memory in those use cases. Learning Objectives: 1. Awareness of performance characteristics of a DRAM-class non-volatile memory in crosspoint and 1T-nR configurations 2. Non-obvious use cases for NRAM 3. Application of non-volatile memory in AI / deep learning engines