Analog AI as a Service: A Cloud Platform for In-Memory Computing
Kaoutar El Maghraoui, Kim Tran, et al.
SSE 2024
Chalcogenide phase change materials enable non-volatile, low-latency storage-class memory. They are also being explored for new forms of computing such as neuromorphic and in-memory computing. A key challenge, however, is the temporal drift in the electrical resistance of the amorphous states that encode data. Drift, caused by the spontaneous structural relaxation of the newly recreated melt-quenched amorphous phase, has consistently been observed to have a logarithmic dependence in time. Here, it is shown that this observation is valid only in a certain observable timescale. Using threshold-switching voltage as the measured variable, based on temperature-dependent and short timescale electrical characterization, the onset of drift is experimentally measured. This additional feature of the structural relaxation dynamics serves as a new benchmark to appraise the different classical models to explain drift.
Kaoutar El Maghraoui, Kim Tran, et al.
SSE 2024
Robert L. Bruce, Syed Ghazi Sarwat, et al.
IRPS 2021
Adnan Mehonic, Daniele Ielmini, et al.
APL Materials
Manuel Le Gallo
NVMTS 2023