Design and Performance Characterization of RADICAL-Pilot on Leadership-Class Platforms

• Published in: IEEE transactions on parallel and distributed systems Vol. 33; no. 4; pp. 818 - 829
• Main Authors: Merzky, Andre, Turilli, Matteo, Titov, Mikhail, Al-Saadi, Aymen, Jha, Shantenu
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.04.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: high performance computing; Leadership; MATHEMATICS AND COMPUTING; Middleware; Parallel processing; Platforms; Programming; python; RADICAL-Pilot; Resource management; Runtime; Supercomputers; Task analysis; Throughput; Workflow management systems; Workload; Workloads
• ISSN: 1045-9219; 1558-2183
• DOI: 10.1109/TPDS.2021.3105994

Many extreme scale scientific applications have workloads comprised of a large number of individual high-performance tasks. The Pilot abstraction decouples workload specification, resource management, and task execution via job placeholders and late-binding. As such, suitable implementations of the Pilot abstraction can support the collective execution of large number of tasks on supercomputers. We introduce RADICAL-Pilot (RP) as a portable, modular and extensible pilot-enabled runtime system. We describe RP's design, architecture and implementation. We characterize its performance and show its ability to scalably execute workloads comprised of tens of thousands heterogeneous tasks on DOE and NSF leadership-class HPC platforms. Specifically, we investigate RP's weak/strong scaling with CPU/GPU, single/multi core, (non)MPI tasks and Python functions when using most of ORNL Summit and TACC Frontera. RADICAL-Pilot can be used stand-alone, as well as the runtime for third-party workflow systems.