Energy-Efficient and Fault-Tolerant Taskgraph Scheduling for Manycores and Grids

Taskgraphs model a broad range of parallel applications. Despite static scheduling, processor failures can be overcome with the help of task duplication, which we explored in a previous proposal. With the advent of processor frequency scaling, energy can be saved by the runtime system as it is informed about gaps in the schedule and task dependencies, and thus can slow down processors as long as dependencies do not lead to a makespan increase. In the case of a fault, a makespan increase can be traded for additional energy investment by accelerating the task duplicates that run tasks from the crashed core. We evaluate our proposal with a large benchmark suite of taskgraphs with different sizes for a generic manycore architecture.