Scalable hardware support for conditional parallelization
Zheng Li, Olivier Certner, José F. Duato, Olivier Temam · 2010
Parallel programming approaches based on task division/spawning are getting increasingly popular because they provide for a simple and elegant abstraction of parallelization, while achieving good performance on workloads which are traditionally complex to parallelize due to the complex control flow and data structures involved. The ability to quickly distribute fine-granularity tasks among many cores is key to the efficiency and scalability of such division-based parallel programming approaches. For this reason, several hardware supports for work stealing environments have already been proposed. However, they all rely on a central hardware structure for distributing tasks among cores, which hampers the scalability and efficiency of these schemes.