The rigid gang task model is based on the idea of executing multiple threads simultaneously on a fixed number of processors to increase efficiency and performance. Although there is extensive literature on global rigid gang scheduling, partitioned approaches have several practical advantages (e.g., task isolation and reduced scheduling overheads). In this paper, we propose a new partitioned scheduling strategy for rigid gang tasks, named strict partitioning. The method creates disjoint partitions of tasks and processors to avoid inter-partition interference. Moreover, it tries to assign tasks with similar volumes (i.e., parallelisms) to the same partition so that the intra-partition interference can be reduced. Within each partition, the tasks can be scheduled using any type of scheduler, which allows the use of a less pessimistic schedulability test. Extensive synthetic experiments and a case study based on Edge TPU benchmarks show that strict partitioning achieves better schedulability performance than state-of-the-art global gang schedulability analyses for both preemptive and non-preemptive rigid gang task sets.

翻译：刚性团伙任务模型基于在固定数量的处理器上同时执行多个线程以提高效率和性能的思想。尽管关于全局刚性团伙调度的文献已相当丰富，但分区方法具有若干实际优势（例如，任务隔离和降低调度开销）。本文针对刚性团伙任务提出了一种新的分区调度策略，称为严格分区。该方法通过创建互不相交的任务与处理器分区来避免分区间的干扰。此外，它尝试将具有相似容量（即并行度）的任务分配到同一分区，从而减少分区内的干扰。在每个分区内部，可使用任意类型的调度器对任务进行调度，这使得能够采用更为乐观的可调度性测试。广泛的合成实验以及基于Edge TPU基准的案例研究表明：对于可抢占和非可抢占的刚性团伙任务集，严格分区在可调度性能上均优于当前最先进的全局团伙可调度性分析方法。