English

Job Management and Task Bundling

High Energy Physics - Lattice 2018-04-18 v1 Distributed, Parallel, and Cluster Computing Computational Physics

Abstract

High Performance Computing is often performed on scarce and shared computing resources. To ensure computers are used to their full capacity, administrators often incentivize large workloads that are not possible on smaller systems. Measurements in Lattice QCD frequently do not scale to machine-size workloads. By bundling tasks together we can create large jobs suitable for gigantic partitions. We discuss METAQ and mpi_jm, software developed to dynamically group computational tasks together, that can intelligently backfill to consume idle time without substantial changes to users' current workflows or executables.

Keywords

Cite

@article{arxiv.1710.01986,
  title  = {Job Management and Task Bundling},
  author = {Evan Berkowitz and Gustav R. Jansen and Kenneth McElvain and André Walker-Loud},
  journal= {arXiv preprint arXiv:1710.01986},
  year   = {2018}
}

Comments

8 pages, 3 figures, LATTICE 2017 proceedings

R2 v1 2026-06-22T22:04:35.181Z