You can use reduced-precision preconditioning if you're writing your own, but there isn't out-of-the-box support. Note that the benefit is limited when working with sparse matrices because a lot of the cost comes from memory access (including column indices) and vectorization for some operations is difficult.
Manuel Valera via petsc-users <petsc-users@mcs.anl.gov> writes: > Hello, > > I was wondering if PETSc had some form of a low precision linear solver > algorithm like seen in: > > https://www.dropbox.com/s/rv5quc3k72qdpmp/iciam_lowprec19.pdf?dl=0 > > I understand this treatment is coming from one of the NAG library > developers, > > Thanks,