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Using Pilot Systems to Execute Many Task Workloads on Supercomputers

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arxiv 1512.08194 v4 pith:IBXY2KVQ submitted 2015-12-27 cs.DC

Andre Merzky , Matteo Turilli , Manuel Maldonado , Mark Santcroos , Shantenu Jha This is my paper · ORCID
classification cs.DC
keywords pilotsystemstasksworkloadscomprisedexecutionperformanceresource
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High performance computing systems have historically been designed to support applications comprised of mostly monolithic, single-job workloads. Pilot systems decouple workload specification, resource selection, and task execution via job placeholders and late-binding. Pilot systems help to satisfy the resource requirements of workloads comprised of multiple tasks. RADICAL-Pilot (RP) is a modular and extensible Python-based pilot system. In this paper we describe RP's design, architecture and implementation, and characterize its performance. RP is capable of spawning more than 100 tasks/second and supports the steady-state execution of up to 16K concurrent tasks. RP can be used stand-alone, as well as integrated with other application-level tools as a runtime system.

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