Title: Temporal correlation detection using computational phase-change memory,
Abstract: For decades, conventional computers based on the von Neumann architecture
have performed computation by repeatedly transferring data between their
processing and their memory units, which are physically separated. As
computation becomes increasingly data-centric and as the scalability limits in
terms of performance and power are being reached, alternative computing
paradigms are searched for in which computation and storage are collocated. A
fascinating new approach is that of computational memory where the physics of
nanoscale memory devices are used to perform certain computational tasks within
the memory unit in a non-von Neumann manner. Here we present a large-scale
experimental demonstration using one million phase-change memory devices
organized to perform a high-level computational primitive by exploiting the
crystallization dynamics. Also presented is an application of such a
computational memory to process real-world data-sets. The results show that
this co-existence of computation and storage at the nanometer scale could be
the enabler for new, ultra-dense, low power, and massively parallel computing
systems.