  We present OpenRBC, a coarse-grained molecular dynamics code, which is
capable of performing an unprecedented in silico experiment --- simulating an
entire mammal red blood cell lipid bilayer and cytoskeleton as modeled by 4
million mesoscopic particles --- using a single shared memory commodity
workstation. To achieve this, we invented an adaptive spatial-searching
algorithm to accelerate the computation of short-range pairwise interactions in
an extremely sparse 3D space. The algorithm is based on a Voronoi partitioning
of the point cloud of coarse-grained particles, and is continuously updated
over the course of the simulation. The algorithm enables the construction of
the key spatial searching data structure in our code, i.e. a lattice-free cell
list, with a time and space cost linearly proportional to the number of
particles in the system. The position and shape of the cells also adapt
automatically to the local density and curvature. The code implements OpenMP
parallelization and scales to hundreds of hardware threads. It outperforms a
legacy simulator by almost an order of magnitude in time-to-solution and more
than 40 times in problem size, thus providing a new platform for probing the
biomechanics of red blood cells.
