How to install MAGEMinApp.jl

First install julia. We recommend that you follow the instructions on how to install Julia from the julia webpage.

Once Julia is installed, open a terminal (Linux, MacOS) or a powershell (Windows) and launch a threaded Julia instance to make use of parallel computation:

julia -t auto

Tip

The number of available threads is machine-dependent. To know how many threads you have you can type the command versioninfo() in a Juliaterminal. The keyword auto will use all you have in your machine. You can also specify the number of threads you want to use, e.g., julia -t 4 for four cores.

julia> using Pkg

julia> Pkg.add("MAGEMinApp")

After the package is installed, one can load the package by using:

julia> using MAGEMinApp

And execute the app as:

julia> App()
[ Info: Listening on: 127.0.0.1:8050, thread id: 1

Now you can open 127.0.0.1:8050 in your favorite web browser.

...and that's it!

Update to newest version

If you have a previous version of MAGEMinApp installed, the easiest way to update MAGEMinApp is the following:

julia>]
pkg> rm MAGEMinApp      # First remove MAGEMinApp
pkg> rm MAGEMin_C       # In case you also use MAGEMin_C this needs to be removed first before updating it, as MAGEMinApp is locked on the last version of MAGEMin_C
pkg> update             # update the repository
pkg> add MAGEMinApp     # reinstall MAGEMin
pkg> up MAGEMinApp      # sometimes needed to update to the last version
(pkg> add MAGEMin_C)    # If you want to have MAGEMin_C too

If you cannot update to the last MAGEMinApp version, try to set the Julia registry to "eager" using the following command, then redo the update process.

julia> ENV["JULIA_PKG_SERVER_REGISTRY_PREFERENCE"] = "eager"

If a new version of MAGEMinApp is available but the update did not work you can try to add the package by providing its version number as:

    julia> ] add MAGEMinApp@x.y.z

where x, y and z are the integers of the version number.

Running MAGEMin_C it in parallel

Julia can be run in parallel using multi-threading. To take advantage of this, you need to start julia from the terminal with:

julia -t auto

which will automatically use all threads on your machine. Alternatively, use julia -t 4 to start it on 4 threads. If you are interested to see what you can do on your machine, type:

versioninfo()
Julia Version 1.9.0
Commit 8e630552924 (2023-05-07 11:25 UTC)
Platform Info:
OS: macOS (arm64-apple-darwin22.4.0)
CPU: 12 × Apple M2 Max
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-14.0.6 (ORCJIT, apple-m1)
Threads: 8 on 8 virtual cores

The function multi_point_minimization will automatically utilize parallelization if you run it on >1 threads.