RADICAL-Pilot (RP) is a Pilot Job
system written in Python. It allows a user to run large numbers of computational
ComputeUnits) concurrently on one or more remote
ComputePilots that RADICAL-Pilot can start transparently on a multitude of
different distributed resources, like HPC clusters and Clouds.
In this model, a part (slice) of a resource is acquired by a user’s application
so that the application can directly schedule
ComputeUnits into that
resource slice, rather than going through the system’s job scheduler. In many
cases, this can drastically shorten overall exeuction time as the individual
ComputeUnits don’t have to wait in the system’s scheduler queue but can
execute directly on the
ComputeUnits are often single-core / multi-threaded executables, but
RADICAL-Pilot also supports execution of parallel executables, for example based
on MPI or OpenMP.
RADICAL-Pilot is not a static system, but it rather provides the user with a programming library (“Pilot-API”) that provides abstractions for resource access and task management. With this library, the user can develop everything from simple “submission scripts” to arbitrarily complex applications, higher- level services and tools.
The RP architecture overview image above shows the main components or RP, and their functional relationships. The RP system will interpret pilot descriptions and submit the respective pilot instances on the target resources. It will then accept unit descriptions and submit those for execution onto the earlier created pilots. The Chapter RADICAL-Pilot Overview will discuss those concepts in some more detail, before then turning to Installation which will describe how RP is deployed and configured, so that the reader can follow the upcoming examples.