A Versatile and Efficient Neuromorphic Platform for Compute-in-Memory with Selector-less Memristive Crossbars

Memristive crossbar arrays have become essential building blocks in the realization of large-scale neuromorphic systems with high-density synaptic connectivity. Traditionally, memristor-based accelerators are equipped with selector elements to reduce cross-talk through sneak paths along unselected lines. However, due to the large drive strength required for selector elements, it comes at the cost of synaptic crossbar density. Selectorless alternatives require careful design of crossbar peripheral circuits to mitigate or eliminate sneak path-induced cross-talk. We propose a hybrid integrated platform that interfaces a selectorless memristor crossbar array with peripheral row and column instrumentation for array-parallel programming and readout for AI learning and inference applications. The proposed switchedcapacitor voltage-sensing instrumentation avoids the need for current-sensing schemes with voltage-clamped sense lines that are typically used to mitigate the sneak path issues in selectorless crossbars but are substantially less energy-efficient than voltage-sensing. Our board-level platform is implemented using commercial off-the-shelf (COTS) data converters and switched capacitors, and is controlled by a Xilinx Spartan-6 FPGA. The system offers programmable sense times to characterize memristors over a wide range of resistances and the capability to switch between a transient-domain measurement and steady-state measurement to offer the desired trade-off between accuracy and energy efficiency during inference parallel readout. We implement a differential weight-encoding scheme to improve the accuracy of matrix-vector multiplication. The system also supports an array-level programming scheme for parallel write access as well as online learning-in-memory for neuromorphic applications through outer-product incremental decomposition of the weight matrix. Thus, our system offers a generic, userconfigurable, and versatile platform to support wide dynamic range measurements of synaptic crossbar arrays and cognitive neuromorphic computing with emerging non-volatile memory devices.