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PSI/J: A Portable Interface for Submitting, Monitoring, and Managing Jobs.

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High-performance computing (HPC) applications face challenges moving between systems due to different schedulers. PSI/J is a new job management API designed to improve portability across diverse HPC environments with minimal overhead.

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Area of Science:

  • High-Performance Computing (HPC)
  • Software Engineering
  • Computational Science

Background:

  • Scientific applications often need to run on different High-Performance Computing (HPC) systems to leverage better hardware or data locality.
  • HPC system portability is hindered by the diversity of job schedulers, complicating application deployment and execution.
  • Existing solutions for managing jobs across different HPC schedulers are insufficient, necessitating a new approach.

Purpose of the Study:

  • To introduce PSI/J, a novel job management abstraction API designed to enhance the portability of software components and applications across various HPC scheduler implementations.
  • To address the need for a standardized API that simplifies the development and deployment of portable scientific applications in heterogeneous HPC environments.
  • To provide a necessary and viable alternative to existing job management solutions in the HPC ecosystem.

Main Methods:

  • Analysis of existing job management APIs in the HPC community to understand factors influencing their design, evolution, and adoption.
  • Design and development of the Portable Scheduler Interface for Java (PSI/J) API based on the insights gained from the analysis of prior systems.
  • Integration of the PSI/J API into three distinct workflow systems and one scientific application to demonstrate its practical applicability.

Main Results:

  • PSI/J has been successfully integrated into multiple workflow systems and a standalone application, validating its practical utility.
  • Experimental results demonstrate that the PSI/J API imposes minimal performance overhead, making it suitable for demanding HPC workloads.
  • The analysis of existing APIs provided a foundation for designing a robust and effective job management abstraction.

Conclusions:

  • PSI/J offers a necessary solution for improving the portability of high-performance computing applications across diverse HPC systems by abstracting scheduler differences.
  • The minimal overhead demonstrated by PSI/J suggests its suitability for integration into production HPC environments without significant performance penalties.
  • The successful integration and experimental validation indicate that PSI/J is a viable and effective tool for simplifying cross-system application deployment in scientific computing.