The International Conference for High Performance Computing, Networking, Storage, and Analysis
The International Conference for High Performance Computing, Networking, Storage, and Analysis
Workshop: PDSW'25: The 10th International Parallel Data Systems Workshop
Authors: Qing Zheng, Brian Atkinson, and Jason Lee (Los Alamos National Laboratory (LANL)); Daoce Wang (University of Nebraska Omaha); and Gary Grider (Los Alamos National Laboratory (LANL))
Abstract: As data volumes grow, the cost of moving large datasets increasingly limits scientific visualization performance. One promising solution is to analyze data where it is stored. This paper presents a pushdown architecture for pNFS-based storage systems that offloads early stages of a VTK pipeline—such as reading and filtering—to the pNFS data servers that hold the data. Using a FUSE-based interface, a pNFS client triggers remote processing and retrieves results by writing and reading special command and result files. Our design leverages pNFS clients' ability to locate file-resident servers, along with a recent Linux enhancement that enables efficient local access to pNFS data without exposing filesystem internals. Offloaded code runs with the user's credentials, preserving standard permission checks. Experiments with two real-world scientific datasets show up to 6.1× speedup in end-to-end visualization runtime and up to 7.1× in data loading, thanks to early data filtering that significantly reduces data movement.
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