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Remove UB from Matrix.h, and replace by quiet NaNs.
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@ -298,9 +298,23 @@ VTKM_EXEC_CONT void MatrixLUPFactorFindUpperTriangleElements(vtkm::Matrix<T, Siz
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vtkm::IdComponent topCornerIndex)
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{
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// Compute values for upper triangle on row topCornerIndex
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for (vtkm::IdComponent colIndex = topCornerIndex + 1; colIndex < Size; colIndex++)
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if (A(topCornerIndex, topCornerIndex) == 0)
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{
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A(topCornerIndex, colIndex) /= A(topCornerIndex, topCornerIndex);
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for (vtkm::IdComponent colIndex = topCornerIndex + 1; colIndex < Size; colIndex++)
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{
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A(topCornerIndex, colIndex) = std::numeric_limits<T>::quiet_NaN();
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}
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}
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else
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{
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// Let's make the reciprocal approximation here.
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// Doesn't make things much fast for small 'Size',
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// but definitely improves performance as 'Size' gets large.
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T rAdiag = 1 / A(topCornerIndex, topCornerIndex);
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for (vtkm::IdComponent colIndex = topCornerIndex + 1; colIndex < Size; colIndex++)
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{
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A(topCornerIndex, colIndex) *= rAdiag;
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}
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}
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// Update the rest of the matrix for calculations on subsequent rows
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@ -314,7 +328,7 @@ VTKM_EXEC_CONT void MatrixLUPFactorFindUpperTriangleElements(vtkm::Matrix<T, Siz
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}
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/// Performs an LUP-factorization on the given matrix using Crout's method. The
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/// LU-factorization takes a matrix A and decomposes it into a lower triangular
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/// LU-factorization takes a matrix A and decomposes it into a lower triangular
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/// matrix L and upper triangular matrix U such that A = LU. The
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/// LUP-factorization also allows permutation of A, which makes the
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/// decomposition always possible so long as A is not singular. In addition to
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@ -389,7 +403,14 @@ VTKM_EXEC_CONT vtkm::Vec<T, Size> MatrixLUPSolve(
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{
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y[rowIndex] -= LU(rowIndex, colIndex) * y[colIndex];
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}
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y[rowIndex] /= LU(rowIndex, rowIndex);
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if (LU(rowIndex, rowIndex) == 0)
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{
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y[rowIndex] = std::numeric_limits<T>::quiet_NaN();
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}
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else
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{
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y[rowIndex] /= LU(rowIndex, rowIndex);
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}
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}
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// Now that we have y, we can easily solve Ux = y for x.
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