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
>
>
