Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Efficient Parallelization for AMR MHD Multiphysics Calculations;
  Implementation in AstroBEAR   Current AMR simulations require algorithms that are highly parallelized and
manage memory efficiently. As compute engines grow larger, AMR simulations will
require algorithms that achieve new levels of efficient parallelization and
memory management. We have attempted to employ new techniques to achieve both
of these goals. Patch or grid based AMR often employs ghost cells to decouple
the hyperbolic advances of each grid on a given refinement level. This
decoupling allows each grid to be advanced independently. In AstroBEAR we
utilize this independence by threading the grid advances on each level with
preference going to the finer level grids. This allows for global load
balancing instead of level by level load balancing and allows for greater
parallelization across both physical space and AMR level. Threading of level
advances can also improve performance by interleaving communication with
computation, especially in deep simulations with many levels of refinement. To
improve memory management we have employed a distributed tree algorithm that
requires processors to only store and communicate local sections of the AMR
tree structure with neighboring processors.

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The categories of this paper are: cmp-lg
32
The categories of this paper are: atom-ph
12
The categories of this paper are: nucl-th
25
The categories of this paper are: patt-sol
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The categories of this paper are: q-alg
11
The categories of this paper are: hep-lat
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The categories of this paper are: q-fin
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The categories of this paper are: alg-geom
9
The categories of this paper are: nlin
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The categories of this paper are: plasm-ph
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The categories of this paper are: funct-an
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The categories of this paper are: eess
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The categories of this paper are: econ
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The categories of this paper are: quant-ph
5
The categories of this paper are: gr-qc
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The categories of this paper are: mtrl-th