Towards Fully Adaptive Pipeline Parallelism for Heterogeneous Distributed Environments

摘要

This work describes an adaptive parallel pipeline skeleton which maps pipeline stages to the best processors available in the system and clears dynamically emerging performance bottlenecks at run-time by re-mapping affected stages to other processors. It is implemented in C and MPI and evaluated on a non-dedicated heterogeneous Linux cluster. We report upon the skeleton's ability to respond to an artificially generated variation in the background load across the cluster.