Reading Nanomagnetic Energy Minimizing Coprocessor

Abstract

Nanomagnetic coprocessor enacts an energy minimization framework to solve the quadratic optimization problem often arisen in a computer vision paradigm. Our approach relies on the fact that the Hamiltonian of a system of coupled nanomagnets is quadratic. Therefore, a wide class of quadratic energy minimization can be solved directly by the relaxation physics of a grid of nanomagnets. The solutions of such problems are obtained from reading the magnetic state of the cells, in other words, the resistance. This monograph explores the methods to detect the magnetic states, and also considers the dimensional variation of each cell of the coprocessor and inspects the resultant change in resistance. We measure at most ${\text{7.8}}$ % change in resistance due to the process imperfection of in-house fabrication processes. This requires a read circuitry that can handle the largest deviation. Unlike STT-MRAM, the circular magnets do not have shape anisotropy but, here we show that with an additional preamplifier circuit, we are able to improve sense margin by at least ${\text{73}}$ %.