Discussion Paper Series in Economics, Department of Economics, Norwegian School of Economics (NHH)
Exploiting Parallelization in Spatial Statistics: an Applied Survey using R.
Abstract: Computing tasks may be parallelized top-down by splitting
into per-node chunks when the tasks permit this kind of division, and
particularly when there is little or no need for communication between the
nodes. Another approach is to parallelize bottom-up, by the substitution of
multi-threaded low-level functions for single-threaded ones in otherwise
unchanged user-level functions. This survey examines the timings of typical
spatial data analysis tasks across a range of data sizes and hardware under
different combinations of these two approaches. Conclusions are drawn
concerning choices of alternatives for parallelization, and attention is
drawn to factors conditioning those choices.
Keywords: Statistical software; Parallelization; Optimized linear algebra subroutines; Multicore processors; Spatial statistics.; (follow links to similar papers)
JEL-Codes: C12; C13; C87; C88; (follow links to similar papers)
16 pages, October 6, 2010
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