OpenCL Task Partitioning in the Presence of GPU Contention
Heterogeneous multi- and many-core systems are increasingly prevalent in the desktop and mobile domains. On these systems it is common for programs to compete with co-running programs for resources. While multi-task scheduling for CPUs is a well-studied area, how to partitioning and map computing tasks onto the heterogeneous system in the presence of GPU contention (i.e. multiple programs compete for the GPU) remains an outstanding problem. In this paper, the authors consider the problem of partitioning OpenCL kernels on a CPU-GPU based system in the presence of contention on the GPU.