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Leveraging Large Language Models to Build and Execute Computational Workflows
SessionThe 18th Workshop on Workflows in Support of Large-Scale Science (WORKS23) - Part 2 of 2
DescriptionThe recent development of large language models (LLMs) with multi-billion parameters, coupled with the creation of user-friendly application programming interfaces (APIs), has paved the way for automatically generating and executing code in response to straightforward human queries. This paper explores how these emerging capabilities can be harnessed to facilitate complex scientific workflows, eliminating the need for traditional coding methods. We present initial findings from our attempt to integrate Phyloflow with OpenAI's function-calling API, and outline a strategy for developing a comprehensive workflow management system based on these concepts.
Author/Presenters
Alejandro Duque
Universidad San Francisco de Quito
Abdullah Syed
University of Missouri, Columbia
Kastan Day
University of Illinois
Matthew Berry
University of Illinois
Daniel S. Katz
University of Illinois
National Center for Supercomputing Applications (NCSA)
Volodymyr Kindratenko
University of Illinois
National Center for Supercomputing Applications (NCSA)
Event Type
Workshop
TimeMonday, 13 November 202310:43am - 10:53am MST
Location704-706
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Tags
Data Analysis, Visualization, and Storage
Large Scale Systems
Programming Frameworks and System Software
Reproducibility
Resource Management
Runtime Systems
Registration Categories
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Delivering Rules-Based Workflows for Science