  Many extreme scale scientific applications have workloads comprised of a
large number of individual high-performance tasks. The Pilot abstraction
decouples workload specification, resource management, and task execution via
job placeholders and late-binding. As such, suitable implementations of the
Pilot abstraction can support the collective execution of large number of tasks
on supercomputers. We introduce RADICAL-Pilot (RP) as a portable, modular and
extensible pilot-enabled runtime system. We describe RP's design, architecture
and implementation. We characterize its performance and show its ability to
scalably execute workloads comprised of tens of thousands heterogeneous tasks
on DOE and NSF leadership-class HPC platforms. Specifically, we investigate
RP's weak/strong scaling with CPU/GPU, single/multi core, (non)MPI tasks and
Python functions when using most of ORNL Summit and TACC Frontera.
RADICAL-Pilot can be used stand-alone, as well as the runtime for third-party
workflow systems.
