Corpus ID: 119102244

METAQ: Bundle Supercomputing Tasks

@article{Berkowitz2017METAQBS,
  title={METAQ: Bundle Supercomputing Tasks},
  author={E. Berkowitz},
  journal={arXiv: Computational Physics},
  year={2017}
}
  • E. Berkowitz
  • Published 2017
  • Computer Science, Physics
  • arXiv: Computational Physics
We describe a light-weight system of bash scripts for efficiently bundling supercomputing tasks into large jobs, so that one can take advantage of incentives or discounts for requesting large allocations. The software can backfill computational tasks, avoiding wasted cycles, and can streamline collaboration between different users. It is simple to use, functioning similarly to batch systems like PBS, MOAB, and SLURM. 
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References

SHOWING 1-2 OF 2 REFERENCES
Walker-Loud, mpi jm, in preparation
  • 2017
METAQ
  • https://github.com/evanberkowitz/metaq
  • 2016