GPU-enhanced architectures are now dominant in HPC systems, but message-passing communication involving GPUs with MPI has proven to be both complex and expensive, motivating new approaches that lower such costs. We compare and contrast stream/graph- and kernel-triggered MPI communication abstractions, whose principal purpose is to enhance the performance of communication when GPU kernels create or consume data for transfer through MPI operations. Researchers and practitioners have proposed multiple potential APIs for stream and/or kernel triggering that span various GPU architectures and approaches, including MPI-4 partitioned point-to-point communication, stream communicators, and explicit MPI stream/queue objects. Designs breaking backward compatibility with MPI are duly noted. Some of these strengthen or weaken the semantics of MPI operations. A key contribution of this paper is to promote community convergence toward a stream- and/or kernel-triggering abstraction by highlighting the common and differing goals and contributions of existing abstractions. We describe the design space in which these abstractions reside, their implicit or explicit use of stream and other non-MPI abstractions, their relationship to partitioned and persistent operations, and discuss their potential for added performance, how usable these abstractions are, and where functional and/or semantic gaps exist. Finally, we provide a taxonomy for stream- and kernel-triggered abstractions, including disambiguation of similar semantic terms, and consider directions for future standardization in MPI-5.

翻译：GPU增强架构现已主导高性能计算系统，但涉及GPU与MPI的消息传递已被证明既复杂又昂贵，这推动了降低此类成本的新方法。我们比较了流/图和内核触发的MPI通信抽象，其主要目的是在GPU内核通过MPI操作创建或消费待传输数据时提升通信性能。研究人员和实践者提出了多种跨越不同GPU架构和方法的流和/或内核触发潜在API，包括MPI-4分区点对点通信、流通信器和显式MPI流/队列对象。我们适当指出了破坏与MPI向后兼容性的设计方案。其中一些方案强化或弱化了MPI操作的语义。本文的关键贡献在于通过凸显现有抽象的共同与不同目标及贡献，促进社区向流和/或内核触发抽象收敛。我们描述了这些抽象所处的设计空间、它们对流及其他非MPI抽象的隐式或显式使用、与分区和持久操作的关系，并讨论了它们提升性能的潜力、这些抽象的可用性，以及功能和/或语义缺口的存在位置。最后，我们提供了流和内核触发抽象的分类法，包括相似语义术语的消歧，并考虑了MPI-5未来标准化的方向。