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Related Experiment Video

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High-resolution Structural Magnetic Resonance Imaging of the Human Subcortex In Vivo and Postmortem

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Hierarchical Storage Management in User Space for Neuroimaging Applications.

Valérie Hayot-Sasson¹, Tristan Glatard²

¹Department of Computer Science and Software Engineering, Concordia University, Montréal, Québec, Canada.

Neuroinformatics

|December 23, 2025

Summary

This summary is machine-generated.

Sea, a new library, optimizes neuroimaging data transfers by intercepting read/write calls. It significantly speeds up data-intensive processing, especially when shared file systems are slow, without impacting performance when systems are not overloaded.

Keywords:

Data management High-performance computing Neuroimaging

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Area of Science:

Neuroscience
Computer Science
Data Science

Background:

Open-data initiatives increase neuroimaging dataset availability.
Processing large datasets shifts bottlenecks to data transfer, challenging existing tools.
Rewriting applications is a barrier to adapting neuroimaging tools for data-intensive processing.

Purpose of the Study:

To develop a library, Sea, for efficient data management in standardized neuroimaging tools.
To minimize data transfer time for large neuroimaging datasets.
To evaluate Sea's performance on high-performance computing clusters.

Main Methods:

Developed Sea, a library to intercept and redirect application read/write calls.
Tested Sea on three neuroimaging preprocessing pipelines.
Evaluated performance on three distinct neuroimaging datasets across two HPC clusters.

Main Results:

Sea achieved speedups up to 32× on deteriorated shared file systems.
Performance remained unaffected when shared file systems were not overburdened.
Sea demonstrated minimal overhead in optimal conditions.

Conclusions:

Sea effectively mitigates data transfer costs in data-intensive neuroimaging analysis.
The library facilitates adaptation of existing tools without complete rewrites.
Sea offers significant performance gains under specific, common, high-load conditions.