MueLu: Cut drop refactor #13282
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MueLu: Cut drop refactor #13282
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cgcgcg
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| typename STS::magnitudeType x_aij = static_cast<SC>(std::fabs(static_cast<double>(rowView.value(x) * rowView.value(x)))); | ||
| typename STS::magnitudeType y_aij = static_cast<SC>(std::fabs(static_cast<double>(rowView.value(y) * rowView.value(y)))); | ||
| typename STS::magnitudeType x_aiiajj = static_cast<SC>(std::fabs(static_cast<double>(threshold * threshold * ghostedDiagValsView(rowView.colidx(x)) * ghostedDiagValsView(row)))); | ||
| typename STS::magnitudeType y_aiiajj = static_cast<SC>(std::fabs(static_cast<double>(threshold * threshold * ghostedDiagValsView(rowView.colidx(y)) * ghostedDiagValsView(row)))); |
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std::fabs might need to be replaced with Kokkos::ArithTraits<impl_scalar_type>::magnitude. We need to think through this a bit for complex scalar type. Same for the other spots where we cast things around.
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July 24, 2024 18:35
Original code within ORIGINAL ifdef. New code within NEW ifdef. DropTol structure marked with KOKKOS_INLINE_FUNCTION and default values are hard coded. Default Algorithm and Cut Drop Algorithm split into separate for loops in NEW code. Cut Drop converted to use Kokkos nested parallel loops. Timers placed in new code and are commented out. Code passes current unit tests. Saw a speedup of about 1.5x with Cuda and 1.2x with Serial when running unit tests with 10,000,000 rows. Signed-off-by: Ian Halim <[email protected]>
DropTol structure in algorithm replaced with new, smaller DropTolKokkos structure. Computations are now done on the fly. Code passes current unit tests. No significant change in speed. Signed-off-by: Ian Halim <[email protected]>
Per Christian's request. DropTolKokkos structure removed and replaced with view indices and view of drop flags. ORIGINAL code removed. BuildKokkos removed. Removed commented out timers. Added comments. Signed-off-by: Ian Halim <[email protected]>
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| typename implATS::magnitudeType y_aij = implATS::magnitude(rowView.value(y) * rowView.value(y)); | ||
| typename implATS::magnitudeType x_aiiajj = implATS::magnitude(threshold * threshold * ghostedDiagValsView(rowView.colidx(x)) * ghostedDiagValsView(row)); | ||
| typename implATS::magnitudeType y_aiiajj = implATS::magnitude(threshold * threshold * ghostedDiagValsView(rowView.colidx(y)) * ghostedDiagValsView(row)); | ||
| return x_aij / x_aiiajj > y_aij / y_aiiajj; |
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| return x_aij / x_aiiajj > y_aij / y_aiiajj; | |
| return (x_aij / x_aiiajj) > (y_aij / y_aiiajj); |
maybe?
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Signed-off-by: Christian Glusa <[email protected]>
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MueLu: Fix clang-format Signed-off-by: Ian Halim <[email protected]>
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@trilinos/muelu
Motivation
This is part of Ian Halim's summer project. Converts an aggregation thresholding algorithm to use Kokkos to make it performance portable. A bonus is that the host-based implementation is now faster.
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Testing
Covered by existing unit tests.