  We describe source code level parallelization for the {\tt kira} direct
gravitational $N$-body integrator, the workhorse of the {\tt starlab}
production environment for simulating dense stellar systems. The
parallelization strategy, called ``j-parallelization'', involves the partition
of the computational domain by distributing all particles in the system among
the available processors. Partial forces on the particles to be advanced are
calculated in parallel by their parent processors, and are then summed in a
final global operation. Once total forces are obtained, the computing elements
proceed to the computation of their particle trajectories. We report the
results of timing measurements on four different parallel computers, and
compare them with theoretical predictions. The computers employ either a
high-speed interconnect, a NUMA architecture to minimize the communication
overhead or are distributed in a grid. The code scales well in the domain
tested, which ranges from 1024 - 65536 stars on 1 - 128 processors, providing
satisfactory speedup. Running the production environment on a grid becomes
inefficient for more than 60 processors distributed across three sites.
