Distributed statistical inference with pyhf enabled through funcX

3 Mar 2021 Matthew Feickert Lukas Heinrich Giordon Stark Ben Galewsky

In High Energy Physics facilities that provide High Performance Computing environments provide an opportunity to efficiently perform the statistical inference required for analysis of data from the Large Hadron Collider, but can pose problems with orchestration and efficient scheduling. The compute architectures at these facilities do not easily support the Python compute model, and the configuration scheduling of batch jobs for physics often requires expertise in multiple job scheduling services... (read more)

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  • DISTRIBUTED, PARALLEL, AND CLUSTER COMPUTING
  • HIGH ENERGY PHYSICS - EXPERIMENT