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June 2022
Book Article
Titel
Using FeFETs as Resistive Synapses in Crossbar-based Analog MAC Accelerating Units
Abstract
Emerging non-volatile memories (eNVMs) face problems such as insufficient ROFF/RON-ratio and limited memory operating window that significantly deteriorate the precision of multiply-accumulate computations (MACs), the core computation of artificial intelligence algorithms, using crossbar-based analogue resistive compute-in-memory (CIM) structures. Properly selecting between single-ended and pseudo-differential structures is the fundamental for the most efficient use of the advantages of a particular eNVM, where, e.g., ferroelectric field-effect-transistors (FeFETs) have a large ROFF/RON-ratio as a great advantage but a significant variability between devices due to the current technology maturity. By investigating and modelling both structures, the results demonstrate that the pseudo-differential structure requires a larger combined operating window from eNVM cells. The reason relies on a statistically enlarged state variation with an increasing number of input channels in the pseudo-differential structure, while the difference between the means of memory's state distributions remains unchanged. Compared to pseudodifferential structures, single-ended structures require a much higher ROFF/RON-ratio from resistance-switching memories, while the requirement for process variation can be relaxed. The results indicate that FeFETs can be well suited to single-ended crossbar-based structures. However, the considerable state variation of FeFETs makes the applications of FeFETs as resistive synapses hard suited into practice. After investigating existing methods, a gate-cascaded synapse with a higher ROFF/RON-ratio and a significantly enlarged operating window is proposed. This article discusses boundary conditions for using eNVMs such as FeFETs in crossbarbased analogue MAC accelerating units from a circuit design perspective.
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Language
English