CAB-MPI: Exploring Interprocess Work-Stealing towards Balanced MPI Communication

Abstract

Load balance is essential for high-performance applications. Unbalanced communication can cause severe performance degradation, even in computation-balanced BSP applications. Designing communication-balanced applications is challenging, however, because of the diverse communication implementations at the underlying runtime system. In this paper, we address this challenge through an interprocess workstealing scheme based on process-memory-sharing techniques. We present CAB-MPI, an MPI implementation that can identify idle processes inside MPI and use these idle resources to dynamically balance communication workload on the node. We design throughput-optimized strategies to ensure efficient stealing of the data movement tasks. We demonstrate the benefit of work stealing through several internal processes in MPI, including intranode data transfer, pack/unpack for noncontiguous communication, and computation in one-sided accumulates. The implementation is evaluated through a set of microbenchmarks and proxy applications on Intel Xeon and Xeon Phi platforms.