Presentation
LangChain-Parsl: Connect Large Language Model Agents to High Performance Computing Resource
SessionAI4S: 6th Workshop on Artificial Intelligence and Machine Learning for Scientific Applications
DescriptionThe Large Language Model (LLM) can improve its performance in answering questions beyond its contextual understanding by running external tools, such as online query for real-time weather, etc. For scientific applications, this enables the LLM to perform and analyze simulation runs for more accurate answers. However, the increasing scale of scientific computing requires the high-performance computers (HPCs), which are managed by job schedulers. In this work, we implemented Parsl to the LangChain tool calling to bridge the gap between the LLM agent and the HPC resource. Two implementations were set up and tested on a local Nvidia GPU workstation and the Polaris/ALCF HPC system. The LLM agent workflow was prompted to run molecular dynamics simulations, with different protein structures and simulation conditions. The results show that our Parsl implementations enabled parallel execution of scientific tools that invoked by LLM agents on both local workstations and HPC platforms.
Author/Presenters
Event Type
Workshop
TimeMonday, 17 November 202510:30am - 10:50am CST
Location274