  Recently, the general synthetic iterative scheme (GSIS) has been proposed to
find the steady-state solution of the Boltzmann equation in the whole range of
gas rarefaction, where its fast-converging and asymptotic-preserving properties
lead to the significant reduction of iteration numbers and spatial cells in the
near-continuum flow regime. However, the efficiency and accuracy of GSIS has
only been demonstrated in two-dimensional problems with small numbers of
spatial cells and discrete velocities. Here, a large-scale parallel computing
strategy is designed to extend the GSIS to three-dimensional flow problems,
including the supersonic flows which are usually difficult to solve by the
discrete velocity method. Since the GSIS involves the calculation of the
mesoscopic kinetic equation which is defined in six-dimensional phase-space,
and the macroscopic high-temperature Navier-Stokes-Fourier equations in
three-dimensional physical space, the proper partition of the spatial and
velocity spaces, and the allocation of CPU cores to the mesoscopic and
macroscopic solvers, are the keys to improving the overall computational
efficiency. These factors are systematically tested to achieve optimal
performance, up to 100 billion spatial and velocity grids. For hypersonic flows
around the Apollo reentry capsule, the X38-like vehicle, and the space station,
our parallel solver can obtain the converged solution within one hour.
