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DTSTAMP:20190719T085744Z
LOCATION:HG E 1.1
DTSTART;TZID=Europe/Stockholm:20190613T171500
DTEND;TZID=Europe/Stockholm:20190613T174500
UID:submissions.pasc-conference.org_PASC19_sess141_msa217@linklings.com
SUMMARY:Efficient Grid- and Data-Reduction Methods for Gyrokinetic Simulat
 ions
DESCRIPTION:Minisymposium\nComputer Science and Applied Mathematics, Physi
 cs\n\nEfficient Grid- and Data-Reduction Methods for Gyrokinetic Simulatio
 ns\n\nJarema, Jenko, Told, Görler\n\nInvestigating plasma microturbulence 
 in magnetic fusion devices with strong radial variations necessitates radi
 ally extended (gyro-)kinetic simulations. This type of simulations is extr
 emely computationally expensive. In grid-based Eulerian codes, one of the 
 main reasons is a very large number of grid points. We present grid- and d
 ata-reduction approaches to tackle this issue. Regarding grid-point reduct
 ion, we introduce block-structured grids in the velocity space, to address
  strong temperature variations across the torus-shaped domain in the radia
 l direction. The new type of grids reuses rectilinear grids and can theref
 ore be easily introduced in existing grid-based gyro-kinetic codes. Regard
 ing data-reduction, we present numerical experiments with compressed stora
 ge of grid-based data. These two approaches were introduced in and tested 
 with the heavily used grid-based code GENE (http://genecode.org). We demon
 strate practical benefits of the grid- and data-reduction techniques: a su
 bstantial reduction in the number of grid-points or storage for the grid-b
 ased data without a significant loss of accuracy, a high speedup, a minima
 l computational overhead, as well as a reduced memory footprint and size o
 f diagnostics data.
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