kmath/kmath-noa/README.md

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2021-06-26 00:36:01 +03:00
# Module kmath-noa
This module provides a `kotlin-jvm` frontend for the
[NOA](https://github.com/grinisrit/noa.git)
library together with relevant functionality from
[LibTorch](https://pytorch.org/cppdocs).
Our aim is to create a Bayesian computational platform
which covers a wide set of applications from particle physics
simulations to deep learning and general differentiable programs
written on top of `AutoGrad` & `ATen`.
2021-06-27 18:28:28 +03:00
## 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`