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2010

Parallel HOP: A Scalable Halo Finder for Massive Cosmological Data Sets

Skory, Stephen, Turk, Matthew J., Norman, Michael L. et al.

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Modern N-body cosmological simulations contain billions ($10^9$) of dark matter particles.

These simulations require hundreds to thousands of gigabytes of memory, and employ hundreds to tens of thousands of processing cores on many compute nodes.
In order to study the distribution of dark matter in a cosmological simulation, the dark matter halos must be identified using a halo finder, which establishes the halo membership of every particle in the simulation.
The resources required for halo finding are similar to the requirements for the simulation itself.

Parallel HOP: A Scalable Halo Finder for Massive Cosmological Data Sets · Around

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Then

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