Efficient Hardware Acceleration of Mean Squared Error Calculation Through In-Memory Computing

Fundamental in numerical computing, mean square (MS) and mean squared error (MSE) calculations play a vital role, especially in artificial intelligence (AI) and signal processing applications. This paper introduces a versatile, low-complexity, and adaptable approach to implement MS and MSE calculations. The central concept involves employing in-memory computing (IMC) technique and executing computations through a set of memristor devices. Specifically, the necessary multiplications and additions leverage the inherent properties of memristor devices, adhering to Ohm's law and Kirchhoff's current law. This innovative method enhances flexibility by programming memristors and emphasizes processing efficiency by reducing computational complexity and latency, surpassing traditional implementation methods.