  Task parallelism as employed by the OpenMP task construct, although ideal for
tackling irregular problems or typical producer/consumer schemes, bears some
potential for performance bottlenecks if locality of data access is important,
which is typically the case for memory-bound code on ccNUMA systems. We present
a programming technique which ameliorates adverse effects of dynamic task
distribution by sorting tasks into locality queues, each of which is preferably
processed by threads that belong to the same locality domain. Dynamic
scheduling is fully preserved inside each domain, and is preferred over
possible load imbalance even if non-local access is required. The effectiveness
of the approach is demonstrated using a blocked six-point stencil solver as a
toy model.
