remove todos

README.md

@@ -6,13 +6,17 @@ This is an experimental project that links the Intel Math Kernel (MKL) as calcul
 
 ## Building
 
-The build scripts are written in Dart so that you need to have a current version of Dart (3.x) installed as well as the `archive`
-library. To install the library, run:
+The build scripts are written in Dart so that you need to have a current version
+of Dart (3.x) installed as well as the `archive` library. To install the
+library, run:
+
 ```bash
 dart pub add archive
 ```
 
-On macOS with Apple M1/M2, one will need to set the Rust toolchain to `stable-x86_64-apple-darwin`:
+On macOS with Apple M1/M2, one will need to set the Rust toolchain to
+`stable-x86_64-apple-darwin`:
+
 ```bash
 rustup install stable-x86_64-apple-darwin
 rustup default stable-x86_64-apple-darwin
@@ -30,20 +34,3 @@ This will download the MKL Python package and its dependencies from pypi.org and
 The Java part has an `MKL` class with the native method-bindings and methods for loading the libraries from a folder. The method `MKL.loadFrom(DIR)` will load the libraries from the folder `{DIR}/olca-mkl-x64_v{VERSION}`. The current version is `1` (the next version would be `2`, then `3` etc.) and it is not the version of the MKL but the version of the openLCA JNI bindings for the MKL. The method `MKL.loadFromDefault()` will try to load the libraries from the openLCA default workspace `~/openLCA-data-1.4/olca-mkl-x64_v{VERSION}`. With the methods `MKL.isLibraryDir` and `MKL.isDefaultLibraryDir` you can also test if a directory contains the MKL library folder with the required libraries (useful for the integration in openLCA later).
 
 **Note** that there is only support for `x64` CPUs, e.g.  on macOS M1/2, you need to run a `x64` JVM using the compatibility layer.
-
-## Python scripts
-
-On macOS Apple M1/M2, one needs to use `python3-intel64`:
-
-```bash
-python3-intel64 -m pip install scipy numpy
-python3-intel64 scripts/pardiso_example.py
-```
-
-## TODO
-
-* test performance on AMD processors (we added a method `mkl_serv_intel_cpu_true`, see https://danieldk.eu/mkl-amd-zen/)
-* test if and how it works on macOS M1/M2 using the x64 compatibility layer
-* move Java part to olca-core (`mkl` branch first) + tests
-* port library download/packaging to the openLCA packager script (maybe with an `--mkl` flag)
-* test in gdt-server containers