The exponential increase in data over the last decade presents a significant challenge to
analytics efforts that seek to process and interpret such data for various applications. Neural-
inspired computing approaches are being developed in order to leverage the computational
properties of the analog, low-power data processing observed in biological systems. Analog
resistive memory crossbars can perform a parallel read or a vector-matrix multiplication as
well as a parallel write or a rank-1 update with high computational efficiency. For an N× N …

… Analog is efficiently and naturally able to combine computation and data access
Effectively, large-scale processing in memory with a multiplier and adder at each real-valued
memory location … If we double the number of resistors, we can double the speed to get the
same energy and SNR. …