The sparse solvers use UMFPACK and CHOLMOD which are C-libraries and thus only support the standard number types. You would need a pure julia written solver that could take any number type.
The stackoverflow error was fixed here: https://github.com/JuliaLang/julia/pull/14902 On Wednesday, August 10, 2016 at 9:47:10 PM UTC+2, Nicklas Andersen wrote: > > Hello > > I'm trying to solve a large, sparse and unsymmetrical linear system Ax = b. > For this task I'm using Julias *SparseMatrixCSC *type for the definition > of my matrices and Julias built in backslash ' \ ' operator for the > solution of the system. > I need *quadruple precision* and thus I've been trying to implement my > routine with the *BigFloat *type together with the SparseMatrixCSC type. > > To illustrate this, I give a simple example here: > set_bigfloat_precision(128); > A = speye(BigFloat, 2, 2); > b = ones(BigFloat, 2, 1); > x = A\b; > > If I do this I either get a StackOverFlow error: > ERROR: StackOverflowError: > in copy at array.jl:100 > in float at sparse/sparsematrix.jl:234 > in call at essentials.jl:57 (repeats 254 times) > > or the solver seems to run forever and never terminates. As the second > error indicates it seems like the sparse solver only accepts the normal > *float* types. > My question is then, is there a way to get quadruple precision with the > standard solvers in Julia, in this case UMFpack I assume ? or should I look > for something else (in this case any suggestions :) ) ? > > Regards Nicklas A. > >
