Scalability-Driven Approaches to Key Aspects of the Message Passing Interface for Next Generation Supercomputing

Abstract

The Message Passing Interface (MPI), which dominates the supercomputing programming environment, is used to orchestrate and fulfill communication in High Performance Computing (HPC). How far HPC programs can scale depends in large part on the ability to achieve fast communication; and to overlap communication with computation or communication with communication. This dissertation proposes a new asynchronous solution to the nonblocking Rendezvous protocol used between pairs of processes to transfer large payloads. On top of enforcing communication/computation overlapping in a comprehensive way, the proposal trumps existing network device-agnostic asynchronous solutions by being memory-scalable and by avoiding brute force strategies. Achieving overlapping between communication and computation is important; but each communication is also expected to generate minimal latency. In that respect, the processing of the queues meant to hold messages pending reception inside the MPI middleware is expected to be fast. Currently though, that processing slows down when program scales grow. This research presents a novel scalability-driven message queue whose processing skips altogether large portions of queue items that are deterministically guaranteed to lead to unfruitful searches. For having little sensitivity to program sizes, the proposed message queue maintains a very good performance, on top of displaying a low and flattening memory footprint growth pattern. Due to the blocking nature of its required synchronizations, the one-sided communication model of MPI creates both communication/computation and communication/communication serializations. This research fixes these issues and latency-related inefficiencies documented for MPI one-sided communications by proposing completely nonblocking and non-serializing versions for those synchronizations. The improvements, meant for consideration in a future MPI standard, also allow new classes of programs to be more efficiently expressed in MPI. Finally, a persistent distributed service is designed over MPI to show its impacts at large scales beyond communication-only activities. MPI is analyzed in situations of resource exhaustion, partial failure and heavy use of internal objects for communicating and non-communicating routines. Important scalability issues are revealed and solution approaches are put forth.