Function cusolverDnIRSParamsSetSolverLowestPrecision 

pub unsafe extern "C" fn cusolverDnIRSParamsSetSolverLowestPrecision(
    params: cusolverDnIRSParams_t,
    solver_lowest_precision: cusolverPrecType_t,
) -> cusolverStatus_t

This function sets the lowest precision that will be used by Iterative Refinement Solver. By lowest precision, we mean the solver is allowed to use as lowest computational precision during the LU factorization process. Note that the user has to set both the main and lowest precision before a first call to the IRS solver because they are NOT set by default with the params structure creation, as it depends on the Input Output data type and user request. Usually the lowest precision defines the speedup that can be achieved. The ratio of the performance of the lowest precision over the main precision (e.g., Inputs/Outputs datatype) define somehow the upper bound of the speedup that could be obtained. More precisely, it depends on many factors, but for large matrices sizes, it is the ratio of the matrix-matrix rank-k product (e.g., GEMM where K is 256 and M=N=size of the matrix) that define the possible speedup. For instance, if the inout precision is real double precision CUSOLVER_R_64F and the lowest precision is CUSOLVER_R_32F, then we can expect a speedup of at most 2X for large problem sizes. If the lowest precision was CUSOLVER_R_16F, then we can expect 3X-4X. A reasonable strategy should take the number of right-hand sides, the size of the matrix as well as the convergence rate into account.

Parameters

• params: The cusolverDnIRSParams_t Params structure.

Return value

• cusolverStatus_t::CUSOLVER_STATUS_IRS_PARAMS_NOT_INITIALIZED: The Params structure was not created.
• cusolverStatus_t::CUSOLVER_STATUS_SUCCESS: The operation completed successfully.