A Reconfigurable Analog Substrate For Highly Efficient Maximum Flow Computation

We present the design and analysis of a novel analog reconfigurable substrate that enables fast and efficient computation of maximum flow on directed graphs. The substrate is composed of memristors and standard analog circuit components, where the on/off states of the crossbar switches encode the graph topology. We show that upon convergence, the steady-state voltages in the circuit capture the solution to the maximum flow problem. We also provide techniques to minimize the impacts of variability and non-ideal circuit components on the solution quality, enabling practical implementation of the proposed substrate. Performance evaluation demonstrates orders of magnitude improvements in speed and energy efficiency compared to a standard CPU implementation.