Analysis of several scheduling algorithms under the nano-threads programming model

Abstract

The authors present the analysis, in a dynamic processor allocation environment, of four scheduling algorithms running on top of the nano-threads programming model. Three of them are well-known: uniform-sized chunking, guided self-scheduling and trapezoid self-scheduling. The fourth is their proposal: adaptable size chunking. In that environment, applications are automatically decomposed into tasks by a parallelizing compiler which uses the hierarchical task graph to represent the source application. The parallel code is an executable representation of this graph with the support of a user-level library (the nano-threads library). The execution environment includes a user-level process (CPU manager) which controls the allocation of processors to applications. The analysis of the scheduling algorithms shows it is possible to provide enough information to the library to allow a fast adaptation to dynamic changes in the processors allocated to the application.