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Building Reproducible Science with Singularity Containers

One of the biggest problems in scientific HPC is ensuring that results are reproducible. That is, the code a scientist runs locally must be able to run identically on any computational resource. Until recently, the job of ensuring that fell to system administrators who needed to manage a complex web of tools and dependencies on those resources. However, with the introduction of HPC containers via Singularity, the ability to mobilize the compute environment has never been easier. Singularity allows anybody to run their own containers on HPC, ushering in a new era of computational mobility, validity, and reproducibility.

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