Abstract: We consider the problem of task reweighting\/ in
fair-scheduled multiprocessor systems wherein each task's processor share is
specified as a weight\/. When a task is reweighted, a new weight is
computed for it, which is then used in future scheduling. Task reweighting can
be used as a means for consuming (or making available) spare processing
capacity. The responsiveness of a reweighting scheme can be assessed by
comparing its allocations to those of an ideal scheduler that can reweight
tasks instantaneously. A reweighting scheme is fine-grained if any
additional per-task "error" (in comparison to an ideal allocation) caused by
a reweighting event is constant. In prior work on uniprocessor\/ notions
of fairness, a number of fine-grained reweighting schemes were proposed.
However, in the multiprocessor case, prior work has failed to produce such a
scheme. In this paper, we remedy this shortcoming by presenting a
multiprocessor reweighting scheme that is fine-grained. We also present an
experimental evaluation of this scheme that shows that it is often much more
responsive than prior (non-fine-grained) schemes in enacting weight-change
requests.