Scheduling Recurrent Precedence-Constrained Task Graphs on a Symmetric Shared-Memory Multiprocessor

We consider approaches that allow task migration for scheduling recurrent directed-acyclic-graph (DAG) tasks on symmetric, shared-memory multiprocessors (SMPs) in order to meet a given throughput requirement with fewer processors. Within the scheduling approach proposed, we present a heuristic based on grouping DAG subtasks for lowering the end-to-end latency and an algorithm for computing an upper bound on latency. Unlike prior work, the purpose of the grouping here is not to map the subtask groups to physical processors, but to generate aggregated entities, each of which can be treated as a single schedulable unit to lower latency. Evaluation using synthetic task sets shows that our approach can lower processor needs considerably while incurring only a modest increase in latency. In contrast to the work presented herein, most prior work on scheduling recurrent DAGs has been for distributed-memory multiprocessors, and has therefore mostly been concerned with statically mapping DAG subtasks to processors.