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DPDispatcher: Scalable HPC Task Scheduling for AI-Driven Science.

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  • 1Department of Physics, University of Alabama at Birmingham, Birmingham, Alabama 35205, United States.

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Summary
This summary is machine-generated.

DPDispatcher is an open-source Python framework for task scheduling in high-performance computing (HPC) environments. It enhances AI-driven workflows by providing scalable, fault-tolerant scheduling, reducing errors and improving automation for scientific computing.

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Area of Science:

  • Computational Science
  • Artificial Intelligence
  • High-Performance Computing

Background:

  • AI is transforming computational science, but AI-driven workflows are complex, spanning diverse HPC systems.
  • Existing workflows face challenges in scalability, fault tolerance, and automation across heterogeneous computing environments.

Purpose of the Study:

  • Introduce DPDispatcher, an open-source Python framework for scalable and fault-tolerant task scheduling.
  • Address the need for robust task management in AI-driven computational science workflows.
  • Improve the portability and automation of scientific computing tasks on HPC systems.

Main Methods:

  • Developed DPDispatcher as a Python framework emphasizing lightweight submission, automatic retries, and robust resumption.
  • Separated connection and file-staging from scheduler control for modularity.
  • Supported multiple HPC job managers and provided local and secure shell (SSH) backends.

Main Results:

  • DPDispatcher has been adopted by over ten scientific packages.
  • Demonstrated use cases in active learning, free-energy calculations, materials screening, and LLM-driven HPC agents.
  • Reduced operational overhead and error rates in scientific computing workflows.

Conclusions:

  • DPDispatcher enhances reliability and automation for high-throughput scientific computing.
  • The framework improves the portability of AI-driven workflows across diverse HPC systems.
  • DPDispatcher facilitates efficient execution of complex computational tasks in scientific research.