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

Andre Merzky, Matteo Turilli, Mikhail Titov, Aymen Al-Saadi, Shantenu Jha

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)818-829
Number of pages12
JournalIEEE Transactions on Parallel and Distributed Systems
Volume33
Issue number4
DOIs
StatePublished - Apr 1 2022

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Hardware and Architecture
  • Computational Theory and Mathematics

Keywords

  • high performance computing
  • Middleware
  • python
  • RADICAL-Pilot

Fingerprint

Dive into the research topics of 'Design and Performance Characterization of RADICAL-Pilot on Leadership-Class Platforms'. Together they form a unique fingerprint.

Cite this