update instructions

This commit is contained in:
Roland Grinis 2021-06-27 16:28:28 +01:00
parent adfb541fff
commit 84937ecaca
2 changed files with 21 additions and 4 deletions

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@ -10,5 +10,22 @@ which covers a wide set of applications from particle physics
simulations to deep learning and general differentiable programs
written on top of `AutoGrad` & `ATen`.
Currently, the native artifacts support only `GNU` and
`CUDA` for GPU acceleration.
## Installation
Currently, to build native artifacts, we support only
the [GNU](https://gcc.gnu.org/) toolchain. For `GPU` kernels, we require a compatible
[CUDA](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html)
installation. If you are on Windows, we recommend setting up
everything on [WSL](https://docs.nvidia.com/cuda/wsl-user-guide/index.html).
To install the library, you have to publish
locally `kmath-core`, `kmath-tensors` with `kmath-noa`:
```
./gradlew -q :kmath-core:publishToMavenLocal :kmath-tensors:publishToMavenLocal :kmath-noa:publishToMavenLocal
```
This builds `jtorch` a JNI wrapper for `NOA/LibTorch`, placed inside:
`~/.konan/third-party/kmath-noa-<version>/cpp-build`

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@ -18,8 +18,8 @@ dependencies {
api(project(":kmath-tensors"))
}
val home = System.getProperty("user.home")
val javaHome = System.getProperty("java.home")
val home: String = System.getProperty("user.home")
val javaHome: String = System.getProperty("java.home")
val thirdPartyDir = "$home/.konan/third-party/kmath-noa-${project.property("version")}"
val cppBuildDir = "$thirdPartyDir/cpp-build"
val cppSources = projectDir.resolve("src/main/cpp")