Scheduling Data-Intensive Tasks on Heterogeneous Many Cores

Scheduling various data-intensive tasks over the processing units of a server has been a heavily studied but still challenging effort. In order to utilize modern multicore servers well, a good scheduling mechanism has to be conscious of different dimensions of parallelism offered by these servers. This requires being aware of the micro-architectural features of processors, the hardware topology connecting the processing units of a server, and the characteristics of these units as well as the data-intensive tasks. The increasing levels of parallelism and heterogeneity in emerging server hardware amplify these challenges in addition to the increasing variety of data-intensive applications. This article first surveys the existing scheduling mechanisms targeting the utilization of a multicore server with uniform processing units. Then, it revisits them in the context of emerging server hardware composed of many diverse cores and identifies the main challenges. Finally, it concludes with the description of a preliminary framework targeting these challenges. Even though this article focuses on data-intensive applications on a single server, many of the challenges and opportunities identified here are not unique to such a setup, and would be relevant to other complex software systems as well as resource-constrained or large-scale hardware platforms.