Hi Kristoffer, First, thanks for this package, it's very useful. After installing the BaseTestNext package I was able to build Pardiso.jl and all tests pass for me. I agree with Jared that BaseTestNext should be included as a dependency. I tested on a small cluster running CentOS 5.11. Julia versioninfo() output is:
Julia Version 0.4.6-pre+7 Commit 273b487* (2016-03-28 14:46 UTC) Platform Info: System: Linux (x86_64-unknown-linux-gnu) CPU: Intel(R) Xeon(R) CPU E5410 @ 2.33GHz WORD_SIZE: 64 BLAS: libmkl_rt LAPACK: libmkl_rt LIBM: libimf LLVM: libLLVM-3.3 I only tested MKL pardiso because I don't have access to pardiso 5.0. My own code that uses Pardiso.jl ran successfully after updating for the function name changes. Cheers, Patrick Belliveau On Tuesday, May 24, 2016 at 1:33:18 AM UTC-7, Kristoffer Carlsson wrote: > > Hello everyone, > > I recently took a bit of time to clean up my wrapper to the linear solver > library Pardiso that exist in MKL and as a standalone project ( > http://www.pardiso-project.org/). It should now hopefully work on both > UNIX and Windows systems and have a decent interface. > > The Pardiso library is commercial software but MKL has academic and > community licenses while Project Pardiso has academic licenses so they are > quite available. > > I would like to tag a new version of it but before I do that it would be > nice if someone else could try it out and see if things work. Since this is > a wrapper to a binary library a lot of things can go wrong and a bit more > battle testing would be very useful. I have run it with passing tests on > two unix machines and one windows but this is of course a very small > configuration space. If anyone is interested, it would be helpful if you > could look at the installation instructions and see if a > Pkg.test("Pardiso") works. Any comments about the interface is also > appreciated. > > Note that the master version is needed: > > Pkg.add("Pardiso") > Pkg.checkout("Pardiso") > > Here is a benchmark solving a (positive definite) system from a > discretized heat problem comparing it to Julias default which in this case > is CHOLMOD: > > julia> nnz(A) > 668656 > > julia> @time factorize(A) \ x > # 3.442693 seconds > > julia> ps = MKLPardisoSolver() > > julia> @time solve(ps, A, x) > # 1.495566 seconds > > Thanks! > > // Kristoffer > >