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FBench: A Flexible Benchmark for CFG-Based What-If Exploration of HPC I/O Patterns
June 29, 2026 ยท Grace Period ยท + Add venue
Authors
Zhaobin Zhu, Chen Wang, Kathryn Mohror, Sarah Neuwirth
arXiv ID
2606.30197
Category
cs.DC: Distributed Computing
Cross-listed
cs.PF
Citations
0
Abstract
The I/O performance of large-scale HPC applications depends on a complex interplay of access patterns, middleware optimizations, and file system configurations. To systematically explore these effects without repeatedly rerunning full applications, we introduce FBench, a flexible and code-transparent benchmarking tool for what-if analysis and I/O performance exploration. FBench leverages context-free grammars (CFGs) derived from Recorder traces to either generate simplified global configuration files for benchmark execution or replay I/O patterns on-the-fly without additional preprocessing. It supports both POSIX and MPI-IO interfaces and allows users to inject optimization hints via JSON configuration files, enabling rapid experimentation with I/O settings without code changes. Our evaluation shows that FBench accurately reproduces I/O behavior for both synthetic and real workloads, capturing access patterns and performance trends across diverse optimizations and file system settings. For IOR and HACC-IO, FBench closely matches scaling behavior and sensitivity to Lustre striping parameters. For FLASH Sedov, it reveals that collective I/O on Lustre can yield up to 30x lower write bandwidth than independent I/O, largely independent of striping, and that switching to a burst buffer file system increases non-collective write bandwidth by about 1.5x without additional tuning. The evaluation with LAMMPS shows that FBench can significantly reduce the time required for what-if analyses and, with simple tuning, enable improvements of up to 8x.
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