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