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Readme for project
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docs/source/index.rst

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projects/RDC.rst
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projects/asymp_conv.rst
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projects/matrixPFASST.rst
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projects/SDC_showdown.rst
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Tests
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.. include:: /../../pySDC/projects/SDC_showdown/README.rst
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Full code: `pySDC/projects/SDC_showdown/SDC_timing_Fisher.py <https://github.com/Parallel-in-Time/pySDC/blob/master/pySDC/projects/SDC_showdown/SDC_timing_Fisher.py>`_
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.. literalinclude:: ../../../pySDC/projects/SDC_showdown/SDC_timing_Fisher.py
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Results:
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.. image:: ../../../data/timings_SDC_variants_Fisher.png
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:scale: 100 %
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Full code: `pySDC/projects/SDC_showdown/SDC_timing_GrayScott.py <https://github.com/Parallel-in-Time/pySDC/blob/master/pySDC/projects/SDC_showdown/SDC_timing_GrayScott.py>`_
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.. literalinclude:: ../../../pySDC/projects/SDC_showdown/SDC_timing_GrayScott.py
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Results:
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.. image:: ../../../data/timings_SDC_variants_GrayScott.png
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:scale: 100 %
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What is the fastest SDC variant?
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================================
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In this project, we test different variants of SDC for a particular problem to see which one is the fastest.
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More precisely, we run SDC for the 1D Fisher equation and the 2D Gray-Scott problem with PETSc data types and solvers, using fully implicit, semi-implicit and multi-implicit time-stepping.
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We also test exact spatial solves vs. inexact ones (aka inexact SDC, ISDC)
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Fisher and Gray-Scott equations
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-------------------------------
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The two run scripts simply test all variants of SDC after the other, each of them exact and then inexact.
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The results are gathered, stored and shown in comparison.
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Note that on standard machines the inexact semi-implicit variant wins each time (may be different for the CI testing).
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.. include:: doc_SDC_showdown.rst
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