GPU accelerated power flow jacobian matrix LU decomposition method
A technology of power flow and matrix, which is applied in the field of LU decomposition of power flow Jacobian matrix, can solve the problems that the program cannot give full play to the advantages of GPU, there is no in-depth optimization of thread design, and the data index method has not been studied in depth, so as to reduce floating point calculation, improve efficiency, and solve the time-consuming effect of power flow calculation
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[0034] Such as image 3 As shown, the LU decomposition method of a GPU-accelerated power flow Jacobian matrix of the present invention, the method includes:
[0035] (1) In the CPU, the LU symbolic decomposition of the Jacobian matrix J is performed to obtain the sparse structure of the lower triangular transformation matrix L and the upper triangular matrix U matrix. The sparse structure of J after the symbolic decomposition is equal to L+U; according to the sparse structure of the U matrix , perform parallelization and layering on each column of matrix J.
[0036] (2) The layered LU decomposition kernel function SparseLU is started in the order of increasing levels in the GPU.
[0037] For the principle of LU symbol decomposition, see: Algorithm 907: KLU, A Direct Sparse Solver for Circuit Simulation Problems, Timothy A. Davis, Ekanathan Palamadai Natarajan, ACM Transactions on Mathematical Software, Vol 37, Issue 6, 2010, pp 36:1-36:17. For the principle of LU layering, p...
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