High Performance Computing~(HPC) software stacks have become complex, with the dependencies of some applications numbering in the hundreds. Packaging, distributing, and administering software stacks of that scale is a complex undertaking anywhere. HPC systems deal with esoteric compilers, hardware, and a panoply of uncommon combinations. In this paper, we explore the mechanisms available for packaging software to find its own dependencies in the context of a taxonomy of software distribution, and discuss their benefits and pitfalls. We discuss workarounds for some common problems caused by using these composed stacks and introduce Shrinkwrap: A solution to producing binaries that directly load their dependencies from precise locations and in a precise order. Beyond simplifying the use of the binaries, this approach also speeds up loading as much as 7x for a large dynamically-linked MPI application in our evaluation.
@article{arxiv.2211.05118,
title = {Mapping Out the HPC Dependency Chaos},
author = {Farid Zakaria and Thomas R. W. Scogland and Todd Gamblin and Carlos Maltzahn},
journal= {arXiv preprint arXiv:2211.05118},
year = {2022}
}
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Presented at SuperComputing 2022 (https://sc22.supercomputing.org/program/)