https://github.com/greendelta/olca-mkl

https://github.com/greendelta/olca-mkl

Last synced: 7 days ago
JSON representation

• Host: GitHub
• URL: https://github.com/greendelta/olca-mkl
• Owner: GreenDelta
• License: mpl-2.0
• Created: 2023-06-09T10:00:17.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2023-07-21T14:55:36.000Z (over 1 year ago)
• Last Synced: 2024-06-11T16:19:44.655Z (7 months ago)
• Language: Rust
• Size: 107 KB
• Stars: 0
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# olca-mkl

This is an experimental project that links the Intel Math Kernel (MKL) as calculation library for openLCA. The chart below shows a performance comparison with UMFPACK for fully solving `A * x = b` for an ecoinvent 3.9 matrix including JNI overhead for communicating between JVM and native memory:

![Performance comparison UMFPACK vs MKL](./performance.png)

## 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:

```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`:

```bash

rustup install stable-x86_64-apple-darwin

rustup default stable-x86_64-apple-darwin

```

Then to build:

```bash

cd olca-mkl

dart build.dart

```

This will download the MKL Python package and its dependencies from pypi.org and extract the native libraries into the `bin` folder. It then compiles the bindings for the Java Native Interface (JNI) which are written in Rust against these libraries. (On Windows, it also generates a lib-file with the exported symbols for the linker first). This should then generate a `(lib)olcamkl.*` library in the `bin` folder.

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.