Flux:克服百亿亿级工作流的调度挑战

D. Ahn, Ned Bass, Albert Chu, J. Garlick, Mark Grondona, Stephen Herbein, Helgi I. Ingólfsson, Joseph Koning, Tapasya Patki, T. Scogland, B. Springmeyer, M. Taufer
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引用次数: 57

摘要

许多针对高端高性能计算系统的新兴科学工作流需要与资源和作业管理软件(RJMS)进行复杂的交互。然而,这些工作流的可移植、高效和易于使用的调度和执行仍然是一个未解决的问题。我们介绍了Flux,这是一种新颖的、分层的RJMS基础设施,它以一种可扩展、易于使用和可移植的方式解决了现代工作流的关键调度挑战。Flux的核心在于它能够无缝地嵌套在其他调度器和它自己创建的批分配中。一旦在每个分配中创建了Flux实例的层次结构,它的一致且丰富的定义良好的api集可移植且有效地支持那些通常具有非传统执行模式的工作流,例如复杂的协同调度需求、小作业的大规模集成以及集成中作业之间的协调。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Flux: Overcoming Scheduling Challenges for Exascale Workflows
Many emerging scientific workflows that target high-end HPC systems require complex interplay with the resource and job management software~(RJMS). However, portable, efficient and easy-to-use scheduling and execution of these workflows is still an unsolved problem. We present Flux, a novel, hierarchical RJMS infrastructure that addresses the key scheduling challenges of modern workflows in a scalable, easy-to-use, and portable manner. At the heart of Flux lies its ability to be nested seamlessly within batch allocations created by other schedulers as well as itself. Once a hierarchy of Flux instance is created within each allocation, its consistent and rich set of well-defined APIs portably and efficiently support those workflows that can often feature non-traditional execution patterns such as requirements for complex co-scheduling, massive ensembles of small jobs and coordination among jobs in an ensemble.
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