- Aug 23, 2019
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Jan Schäfer authored
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Jan Schäfer authored
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Jakub Klinkovský authored
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Jan Schäfer authored
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Jakub Klinkovský authored
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Jan Schäfer authored
mended AUSM+ diff. operator
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Jan Schäfer authored
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root authored
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Jan Schäfer authored
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Jan Schäfer authored
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Jan Schäfer authored
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Jan Schäfer authored
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Jan Schäfer authored
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Jan Schäfer authored
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Jan Schäfer authored
added solver containing Steger-Warming, Van Leer and Lax Friedrich in one for Euler and Navier-Stokes
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- Aug 17, 2019
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Jakub Klinkovský authored
Fixes #43
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Jakub Klinkovský authored
PrefixSum: separate first and second phase for OpenMP implementation and expose performFirstPhase and performSecondPhase methods
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Jakub Klinkovský authored
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Jakub Klinkovský authored
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Jakub Klinkovský authored
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Jakub Klinkovský authored
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Jakub Klinkovský authored
Same changes as for the regular Reduction operation...
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Jakub Klinkovský authored
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Jakub Klinkovský authored
Fixes #42
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Jakub Klinkovský authored
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Jakub Klinkovský authored
Benchmarks can be easily profiled even without this parameter, so it was just an unnecessary complication.
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Jakub Klinkovský authored
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Jakub Klinkovský authored
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Jakub Klinkovský authored
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Jakub Klinkovský authored
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Jakub Klinkovský authored
This is nicer because it more clearly separates data load, computation and data store. Furthermore, it allows to use instances of std::plus, std::logical_and, std::logical_or, etc. instead of custom lambda functions.
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Jakub Klinkovský authored
It contained only methods for prefixSum and segmentedPrefixSum, which were identical for Host and Cuda, so they can be easily implemented directly in Vector and VectorView.
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Jakub Klinkovský authored
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Jakub Klinkovský authored
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Jakub Klinkovský authored
The performance seems to be identical to the code using volatile.
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Jakub Klinkovský authored
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Jakub Klinkovský authored
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Jakub Klinkovský authored
They are not implemented anyway...
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Jakub Klinkovský authored
This is necessary to be able to run tests in parallel.
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Jakub Klinkovský authored
The build takes too long because of this and nobody uses it anyway. CUDA does not support long double in device code at all.
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