As modern HPC applications and systems advance to exascale, their complexity and the need for more efficient resource utilization increases. This fact demands more advanced monitoring, analysis and optimization approaches. Therefore, the Message Passing Interface (MPI), which is the most common parallel programming system for HPC applications, must enable these advanced approaches. Even if the existing MPI Profiling Interface, PMPI, provides comprehensive tool support, it is no longer sufficient to enable these advanced approaches. In particular, PMPI does not support simultaneous or collaborative monitoring solutions from multiple different agents or sources. In this paper we introduce our interface QMPI, which addresses these limitations of PMPI and aims to be a successor to it. This paper presents the use cases and requirements that necessitate the development of QMPI, as well as a design offer for a QMPI prototype followed by its implementation and evaluation.

随着现代HPC应用程序和系统的扩展至万亿级，其复杂性和对更有效资源利用的需求也在增加。这一事实需要更高级的监视，分析和优化方法。因此，消息传递接口（MPI）是HPC应用程序中最常见的并行编程系统，必须启用这些高级方法。即使现有的MPI分析界面PMPI提供了全面的工具支持，也不足以启用这些高级方法。特别是，PMPI不支持来自多个不同代理或来源的同时或协作监视解决方案。在本文中，我们介绍了接口QMPI，它解决了PMPI的这些局限性，并旨在成为其继任者。