Dynamic dataflow machines exploit parallelism among loop iterations by loop unraveling: all
iterations of the loop are started together and operations in various iterations execute when
their input data are present. Unbounded loop unraveling can strain the resources available
on the machine and, in extreme cases, deadlock can occur due to overcommitment of
resources. Previous efforts to address this problem have focused mainly on run-time
mechanisms of debatable utility. Loop bounding, a compile-time technique, controls …

Dataflow machines can “unravel” loops automatically so that many iterations of a loop can
execute in parallel. Unbounded loop unraveling can strain the resources available on the
machine and, in extreme cases, deadlock can occur due to overcommitment of resources.
Previous efforts to address this problem have focused mainly on runtime mechanisms of
debatable utility. Loop bounding, a compile-time technique, controls parallelism by
introducing dependencies between loop iterations. The loop is given enough resources for …