Resumen
In this research we are considering the benchmarking of batched matrix inversion and solution of linear systems. The problem of multiple matrix inversion with the same fill sparsity is usually considered in problems of fluid mechanics with chemistry. In this case the system is stiff, and an implicit method is required to solve the problem. The core of such method is the multiple matrix inversion. We benchmark different methods based on cuSPARSE and MAGMA libraries and CPU LAPACK version depending on the matrix filling. We also provide our own experimental code that implements GaussJordan elimination on GPU using register shuffle. It is shown that the fastest method is the QR matrix inversion for single precision calculations. We also show that the suggested Gauss?Jordan elimination method looks promising being about 8?10 times faster than cuSPARSE QR method. We also demonstrate the application of batch solvers in the coupled reactive flow problem.