Dynamic Loop Scheduling Using the MPI Passive-Target Remote Memory Access Model

Large parallel loops are present in many scientific applications. Static and dynamic loop scheduling (DLS) techniques aim to achieve load balanced executions of applications. The use of DLS techniques in scientific applications, such as the self-scheduling-based techniques, showed significant performance advantages compared to static techniques. On distributed-memory systems, DLS techniques have been implemented using the message-passing interface (MPI). Existing implementations of MPI-based DLS libraries do not consider the novel features of the latest MPI standards, such as one-sided communication, shared-memory window creation, and atomic read-modify-write operations. This poster considers these features and proposes an MPI-based DLS library written in the C language. Unlike existing libraries, the proposed DLS library does not employ a master-worker execution model. Moreover, it contains implementations of five well-known DLS techniques, namely self-scheduling, fixed-size chunking, guided self-scheduling, trapezoid self-scheduling, and factoring. An application from the computer vision is used to assess and compare the performance of the proposed library against the performance of existing solutions. The evaluation results show improved performance and highlight the need to revise and upgrade existing solutions in light of the significant advancements in the MPI standards.