We evaluate the performance of different algorithms in minimizing the\nHamiltonian of a spatial-photonic Ising machine (SPIM). We then encode the\nnumber-partitioning problem on the SPIM and adiabatically arrive at good\nsolutions for the problem for over 16000 spins, with a time complexity that\nonly scales linearly with problem size. Finally, we benchmark our machine\nperformance against the classical solver, Gurobi, and also a D-Wave 5000+\nquantum annealer. With just one spatial light modulator, and and adiabatic\nevolution scheme for the phase, our results surpass current state-of-the-art\nSPIMs. We reduce hardware costs, and can solve larger problems more\nefficiently.\n