  Boson sampling is expected to be one of an important milestones that will
demonstrate quantum supremacy. The present work establishes the benchmarking of
Gaussian boson sampling (GBS) with threshold detection based on the Sunway
TaihuLight supercomputer. To achieve the best performance and provide a
competitive scenario for future quantum computing studies, the selected
simulation algorithm is fully optimized based on a set of innovative
approaches, including a parallel scheme and instruction-level optimizing
method. Furthermore, data precision and instruction scheduling are handled in a
sophisticated manner by an adaptive precision optimization scheme and a
DAG-based heuristic search algorithm, respectively. Based on these methods, a
highly efficient and parallel quantum sampling algorithm is designed. The
largest run enables us to obtain one Torontonian function of a 100 x 100
submatrix from 50-photon GBS within 20 hours in 128-bit precision and 2 days in
256-bit precision.
